Novel Methods For Robust Real Time Hand Gesture Interfaces

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Novel Methods for Robust Real-time Hand Gesture Interfaces

Author : Nathaniel Sean Rossol
Publisher :
ISBN 13 :
Total Pages : 110 pages
Book Rating : 4.:/5 (959 download)

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Book Synopsis Novel Methods for Robust Real-time Hand Gesture Interfaces by : Nathaniel Sean Rossol

Download or read book Novel Methods for Robust Real-time Hand Gesture Interfaces written by Nathaniel Sean Rossol and published by . This book was released on 2015 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-time control of visual display systems via mid-air hand gestures offers many advantages over traditional interaction modalities. In medicine, for example, it allows a practitioner to adjust display values, e.g. contrast or zoom, on a medical visualization interface without the need to re-sterilize the interface. However, there are many practical challenges that make such interfaces non-robust including poor tracking due to frequent occlusion of fingers, interference from hand-held objects, and complex interfaces that are difficult for users to learn to use efficiently. In this work, various techniques are explored for improving the robustness of computer interfaces that use hand gestures. This work is focused predominately on real-time markerless Computer Vision (CV) based tracking methods with an emphasis on systems with high sampling rates. First, we explore a novel approach to increase hand pose estimation accuracy from multiple sensors at high sampling rates in real-time. This approach is achieved through an intelligent analysis of pose estimations from multiple sensors in a way that is highly scalable because raw image data is not transmitted between devices. Experimental results demonstrate that our proposed technique significantly improves the pose estimation accuracy while still maintaining the ability to capture individual hand poses at over 120 frames per second. Next, we explore techniques for improving pose estimation for the purposes of gesture recognition in situations where only a single sensor is used at high sampling rates without image data. In this situation, we demonstrate an approach where a combination of kinematic constraints and computed heuristics are used to estimate occluded keypoints to produce a partial pose estimation of a user's hand which is then used with our gestures recognition system to control a display. The results of our user study demonstrate that the proposed algorithm significantly improves the gesture recognition rate of the setup. We then explore gesture interface designs for situations where the user may (or may not) have a large portion of their hand occluded by a hand-held tool while gesturing. We address this challenge by developing a novel interface that uses a single set of gestures designed to be equally effective for fingers and hand-held tools without the need for any markers. The effectiveness of our approach is validated through a user study on a group of people given the task of adjusting parameters on a medical image display. Finally, we examine improving the efficiency of training for our interfaces by automatically assessing key user performance metrics (such as dexterity and confidence), and adapting the interface accordingly to reduce user frustration. We achieve this through a framework that uses Bayesian networks to estimate values for abstract hidden variables in our user model, based on analysis of data recorded from the user during operation of our system.

Robust Hand Gesture Recognition for Robotic Hand Control

Author : Ankit Chaudhary
Publisher : Springer
ISBN 13 : 9811047987
Total Pages : 108 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Robust Hand Gesture Recognition for Robotic Hand Control by : Ankit Chaudhary

Download or read book Robust Hand Gesture Recognition for Robotic Hand Control written by Ankit Chaudhary and published by Springer. This book was released on 2017-06-05 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on light invariant bare hand gesture recognition while there is no restriction on the types of gestures. Observations and results have confirmed that this research work can be used to remotely control a robotic hand using hand gestures. The system developed here is also able to recognize hand gestures in different lighting conditions. The pre-processing is performed by developing an image-cropping algorithm that ensures only the area of interest is included in the segmented image. The segmented image is compared with a predefined gesture set which must be installed in the recognition system. These images are stored and feature vectors are extracted from them. These feature vectors are subsequently presented using an orientation histogram, which provides a view of the edges in the form of frequency. Thereby, if the same gesture is shown twice in different lighting intensities, both repetitions will map to the same gesture in the stored data. The mapping of the segmented image's orientation histogram is firstly done using the Euclidian distance method. Secondly, the supervised neural network is trained for the same, producing better recognition results. An approach to controlling electro-mechanical robotic hands using dynamic hand gestures is also presented using a robot simulator. Such robotic hands have applications in commercial, military or emergency operations where human life cannot be risked. For such applications, an artificial robotic hand is required to perform real-time operations. This robotic hand should be able to move its fingers in the same manner as a human hand. For this purpose, hand geometry parameters are obtained using a webcam and also using KINECT. The parameter detection is direction invariant in both methods. Once the hand parameters are obtained, the fingers’ angle information is obtained by performing a geometrical analysis. An artificial neural network is also implemented to calculate the angles. These two methods can be used with only one hand, either right or left. A separate method that is applicable to both hands simultaneously is also developed and fingers angles are calculated. The contents of this book will be useful for researchers and professional engineers working on robotic arm/hand systems.

Real-time 2D Static Hand Gesture Recognition and 2D Hand Tracking for Human-Computer Interaction

Author : Pavel Alexandrovich Popov
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Real-time 2D Static Hand Gesture Recognition and 2D Hand Tracking for Human-Computer Interaction by : Pavel Alexandrovich Popov

Download or read book Real-time 2D Static Hand Gesture Recognition and 2D Hand Tracking for Human-Computer Interaction written by Pavel Alexandrovich Popov and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The topic of this thesis is Hand Gesture Recognition and Hand Tracking for user interface applications. 3 systems were produced, as well as datasets for recognition and tracking, along with UI applications to prove the concept of the technology. These represent significant contributions to resolving the hand recognition and tracking problems for 2d systems. The systems were designed to work in video only contexts, be computationally light, provide recognition and tracking of the user's hand, and operate without user driven fine tuning and calibration. Existing systems require user calibration, use depth sensors and do not work in video only contexts, or are computationally heavy requiring GPU to run in live situations. A 2-step static hand gesture recognition system was created which can recognize 3 different gestures in real-time. A detection step detects hand gestures using machine learning models. A validation step rejects false positives. The gesture recognition system was combined with hand tracking. It recognizes and then tracks a user's hand in video in an unconstrained setting. The tracking uses 2 collaborative strategies. A contour tracking strategy guides a minimization based template tracking strategy and makes it real-time, robust, and recoverable, while the template tracking provides stable input for UI applications. Lastly, an improved static gesture recognition system addresses the drawbacks due to stratified colour sampling of the detection boxes in the detection step. It uses the entire presented colour range and clusters it into constituent colour modes which are then used for segmentation, which improves the overall gesture recognition rates. One dataset was produced for static hand gesture recognition which allowed for the comparison of multiple different machine learning strategies, including deep learning. Another dataset was produced for hand tracking which provides a challenging series of user scenarios to test the gesture recognition and hand tracking system. Both datasets are significantly larger than other available datasets. The hand tracking algorithm was used to create a mouse cursor control application, a paint application for Android mobile devices, and a FPS video game controller. The latter in particular demonstrates how the collaborating hand tracking can fulfill the demanding nature of responsive aiming and movement controls.

Image Analysis

Author : Bjarne K. Ersboll
Publisher : Springer
ISBN 13 : 3540730400
Total Pages : 1001 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Image Analysis by : Bjarne K. Ersboll

Download or read book Image Analysis written by Bjarne K. Ersboll and published by Springer. This book was released on 2007-07-03 with total page 1001 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th Scandinavian Conference on Image Analysis, SCIA 2007, held in Aalborg, Denmark in June 2007. It covers computer vision, 2D and 3D reconstruction, classification and segmentation, medical and biological applications, appearance and shape modeling, face detection, tracking and recognition, motion analysis, feature extraction and object recognition.

Real-Time Vision for Human-Computer Interaction

Author : Branislav Kisacanin
Publisher : Springer Science & Business Media
ISBN 13 : 0387278907
Total Pages : 308 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Real-Time Vision for Human-Computer Interaction by : Branislav Kisacanin

Download or read book Real-Time Vision for Human-Computer Interaction written by Branislav Kisacanin and published by Springer Science & Business Media. This book was released on 2005-12-06 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 200Ts Vision of Vision One of my formative childhood experiences was in 1968 stepping into the Uptown Theater on Connecticut Avenue in Washington, DC, one of the few movie theaters nationwide that projected in large-screen cinerama. I was there at the urging of a friend, who said I simply must see the remarkable film whose run had started the previous week. "You won't understand it," he said, "but that doesn't matter. " All I knew was that the film was about science fiction and had great special eflPects. So I sat in the front row of the balcony, munched my popcorn, sat back, and experienced what was widely touted as "the ultimate trip:" 2001: A Space Odyssey. My friend was right: I didn't understand it. . . but in some senses that didn't matter. (Even today, after seeing the film 40 times, I continue to discover its many subtle secrets. ) I just had the sense that I had experienced a creation of the highest aesthetic order: unique, fresh, awe inspiring. Here was a film so distinctive that the first half hour had no words whatsoever; the last half hour had no words either; and nearly all the words in between were banal and irrelevant to the plot - quips about security through Voiceprint identification, how to make a phonecall from a space station, government pension plans, and so on.

Robust Real-time Hand Tracking and Gesture Recognition Using Smart Snakes

Author : Tony Heap
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (66 download)

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Book Synopsis Robust Real-time Hand Tracking and Gesture Recognition Using Smart Snakes by : Tony Heap

Download or read book Robust Real-time Hand Tracking and Gesture Recognition Using Smart Snakes written by Tony Heap and published by . This book was released on 1995 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Dual-sensor Approaches for Real-time Robust Hand Gesture Recognition

Author : Kui Liu
Publisher :
ISBN 13 :
Total Pages : 198 pages
Book Rating : 4.:/5 (921 download)

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Book Synopsis Dual-sensor Approaches for Real-time Robust Hand Gesture Recognition by : Kui Liu

Download or read book Dual-sensor Approaches for Real-time Robust Hand Gesture Recognition written by Kui Liu and published by . This book was released on 2015 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of hand gesture recognition has been steadily growing in various human-computer interaction applications. Under realistic operating conditions, it has been shown that hand gesture recognition systems exhibit recognition rate limitations when using a single sensor. Two dual-sensor approaches have thus been developed in this dissertation in order to improve the performance of hand gesture recognition under realistic operating conditions. The first approach involves the use of image pairs from a stereo camera setup by merging the image information from the left and right camera, while the second approach involves the use of a Kinect depth camera and an inertial sensor by fusing differing modality data within the framework of a hidden Markov model. The emphasis of this dissertation has been on system building and practical deployment. More specifically, the major contributions of the dissertation are: (a) improvement of hand gestures recognition rates when using a pair of images from a stereo camera compared to when using a single image by fusing the information from the left and right images in a complementary manner, and (b) improvement of hand gestures recognition rates when using a dual-modality sensor setup consisting of a Kinect depth camera and an inertial body sensor compared to the situations when each sensor is used individually on its own. Experimental results obtained indicate that the developed approaches generate higher recognition rates in different backgrounds and lighting conditions compared to the situations when an individual sensor is used. Both approaches are designed such that the entire recognition system runs in real-time on PC platform.

Human-Computer Interaction. Novel Interaction Methods and Techniques

Author : Julie A. Jacko
Publisher : Springer Science & Business Media
ISBN 13 : 3642025773
Total Pages : 923 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Human-Computer Interaction. Novel Interaction Methods and Techniques by : Julie A. Jacko

Download or read book Human-Computer Interaction. Novel Interaction Methods and Techniques written by Julie A. Jacko and published by Springer Science & Business Media. This book was released on 2009-07-14 with total page 923 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 13th International Conference on Human–Computer Interaction, HCI Inter- tional 2009, was held in San Diego, California, USA, July 19–24, 2009, jointly with the Symposium on Human Interface (Japan) 2009, the 8th International Conference on Engineering Psychology and Cognitive Ergonomics, the 5th International Conference on Universal Access in Human–Computer Interaction, the Third International Conf- ence on Virtual and Mixed Reality, the Third International Conference on Internati- alization, Design and Global Development, the Third International Conference on Online Communities and Social Computing, the 5th International Conference on Augmented Cognition, the Second International Conference on Digital Human Mod- ing, and the First International Conference on Human Centered Design. A total of 4,348 individuals from academia, research institutes, industry and gove- mental agencies from 73 countries submitted contributions, and 1,397 papers that were judged to be of high scientific quality were included in the program. These papers - dress the latest research and development efforts and highlight the human aspects of design and use of computing systems. The papers accepted for presentation thoroughly cover the entire field of human–computer interaction, addressing major advances in the knowledge and effective use of computers in a variety of application areas.

Robust Real-time Hands-and-face Detection for Human Robot Interaction

Author : SeyedMehdi MohaimenianPour
Publisher :
ISBN 13 :
Total Pages : 91 pages
Book Rating : 4.:/5 (112 download)

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Book Synopsis Robust Real-time Hands-and-face Detection for Human Robot Interaction by : SeyedMehdi MohaimenianPour

Download or read book Robust Real-time Hands-and-face Detection for Human Robot Interaction written by SeyedMehdi MohaimenianPour and published by . This book was released on 2018 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: With recent advances, robots have become more affordable and intelligent, which expands their application domain and number of consumers. Having robots around us in our daily lives creates a demand for an interaction system for communicating humans' intentions and commands to robots. We are interested in interactions that are easy, intuitive, and do not require the human to use any additional equipment. We present a robust real-time system for visual detection of hands and faces in RGB and gray-scale images based on a Deep Convolutional Neural Network. This system is designed to meet the requirements of a hands-free interface to UAVs described below that could be used for communicating to other robots equipped with a monocular camera using only hands and face gestures without any extra instruments. This work is accompanied by a novel hands-and-faces detection dataset gathered and labelled from a wide variety of sources including our own Human-UAV interaction videos, and several third-party datasets. By training our model on all these data, we obtain qualitatively good detection results in terms of both accuracy and speed on a commodity GPU. The same detector gives state-of-the-art accuracy and speed in a hand-detection benchmark and competitive results in a face detection benchmark. To demonstrate its effectiveness for Human-Robot Interaction we describe its use as the input to a novel, simple but practical gestural Human-UAV interface for static gesture detection based on hand position relative to the face. A small vocabulary of hand gestures is used to demonstrate our end-to-end pipeline for un-instrumented human-UAV interaction useful for entertainment or industrial applications. All software, training and test data produced for this thesis is released as an Open Source contribution.

Pattern Recognition

Author : José Francisco Martínez-Trinidad
Publisher : Springer
ISBN 13 : 3319393936
Total Pages : 366 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Pattern Recognition by : José Francisco Martínez-Trinidad

Download or read book Pattern Recognition written by José Francisco Martínez-Trinidad and published by Springer. This book was released on 2016-06-15 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th Mexican Conference on Pattern Recognition, MCPR 2016, held in Guanajuato, Mexico, in June 2016. The 34 revised full papers presented were carefully reviewed and selected from 60 submissions. The papers are organized in topical sections on computer vision and image analysis; pattern recognition and artificial intelligent techniques; signal processing and analysis; and applications of pattern recognition.

Markov Models for Pattern Recognition

Author : Gernot A. Fink
Publisher : Springer Science & Business Media
ISBN 13 : 1447163087
Total Pages : 275 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Markov Models for Pattern Recognition by : Gernot A. Fink

Download or read book Markov Models for Pattern Recognition written by Gernot A. Fink and published by Springer Science & Business Media. This book was released on 2014-01-14 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.

Real-time Dynamic Hand Shape Gesture Controller

Author : Rajesh Radhakrishnan
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (796 download)

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Book Synopsis Real-time Dynamic Hand Shape Gesture Controller by : Rajesh Radhakrishnan

Download or read book Real-time Dynamic Hand Shape Gesture Controller written by Rajesh Radhakrishnan and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this thesis is to build a real time gesture recognition system which can spot and recognize specific gestures from continuous stream of input video. We address the recognition of single handed dynamic gestures. We have considered gestures which are sequences of distinct hand poses. Gestures are classified based on their hand poses and its nature of motion. The recognition strategy uses a combination of spatial hand shape recognition using chamfer distance measure and temporal characteristics through dynamic programming. The system is fairly robust to background clutter and uses skin color for tracking. Gestures are an important modality for human-machine communication, and robust gesture recognition can be an important component of intelligent homes and assistive environments in general. Challenging task in a robust recognition system is the amount of unique gesture classes that the system can recognize accurately. Our problem domain is two dimensional tracking and recognition with a single static camera. We also address the reliability of the system as we scale the size of gesture vocabulary. Our system is based on supervised learning, both detection and recognition uses the existing trained models. The hand tracking framework is based on non-parametric histogram bin based approach. A coarser histogram bin containing skin and non-skin models of size 32x32x32 was built. The histogram bins were generated by using samples of skin and non-skin images. The tracker framework effectively finds the moving skin locations as it integrates both the motion and skin detection. Hand shapes are another important modality of our gesture recognition system. Hand shapes can hold important information about the meaning of a gesture, or about the intent of an action. Recognizing hand shapes can be a very challenging task, because the same hand shape may look very different in different images, depending on the view point of the camera. We use chamfer matching of edge extracted hand regions to compute the minimum chamfer matching score. Dynamic Programming technique is used align the temporal sequences of gesture. In this paper, we propose a novel hand gesture recognition system where in user can specify his/her desired gestures vocabulary. The contributions made to the gesture recognition framework are, user-chosen gesture vocabulary (i.e) user is given an option to specify his/her desired gesture vocabulary, confusability analysis of gesture (i.e) During training, if user provides similar gesture pattern for two different gesture patterns the system automatically alerts the user to provide a different gesture pattern for a specific class, novel methodology to combine both hand shape and motion trajectory for recognition, hand tracker (using motion and skin color detection) aided hand shape recognition. The system runs in real time with frame rate of 15 frames per second in debug mode and 17 frames per second in release mode. The system was built in a normal hardware configuration with Microsoft Visual Studio, using OpenCV and C++. Experimental results establish the effectiveness of the system.

Challenges and Applications for Hand Gesture Recognition

Author : Kane, Lalit
Publisher : IGI Global
ISBN 13 : 1799894363
Total Pages : 249 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Challenges and Applications for Hand Gesture Recognition by : Kane, Lalit

Download or read book Challenges and Applications for Hand Gesture Recognition written by Kane, Lalit and published by IGI Global. This book was released on 2022-03-25 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the rise of new applications in electronic appliances and pervasive devices, automated hand gesture recognition (HGR) has become an area of increasing interest. HGR developments have come a long way from the traditional sign language recognition (SLR) systems to depth and wearable sensor-based electronic devices. Where the former are more laboratory-oriented frameworks, the latter are comparatively realistic and practical systems. Based on various gestural traits, such as hand postures, gesture recognition takes different forms. Consequently, different interpretations can be associated with gestures in various application contexts. A considerable amount of research is still needed to introduce more practical gesture recognition systems and associated algorithms. Challenges and Applications for Hand Gesture Recognition highlights the state-of-the-art practices of HGR research and discusses key areas such as challenges, opportunities, and future directions. Covering a range of topics such as wearable sensors and hand kinematics, this critical reference source is ideal for researchers, academicians, scholars, industry professionals, engineers, instructors, and students.

Real-time Hand Gesture Detection and Recognition for Human Computer Interaction

Author : Nasser Hasan Abdel-Qader Dardas
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (871 download)

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Book Synopsis Real-time Hand Gesture Detection and Recognition for Human Computer Interaction by : Nasser Hasan Abdel-Qader Dardas

Download or read book Real-time Hand Gesture Detection and Recognition for Human Computer Interaction written by Nasser Hasan Abdel-Qader Dardas and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis focuses on bare hand gesture recognition by proposing a new architecture to solve the problem of real-time vision-based hand detection, tracking, and gesture recognition for interaction with an application via hand gestures. The first stage of our system allows detecting and tracking a bare hand in a cluttered background using face subtraction, skin detection and contour comparison. The second stage allows recognizing hand gestures using bag-of-features and multi-class Support Vector Machine (SVM) algorithms. Finally, a grammar has been developed to generate gesture commands for application control. Our hand gesture recognition system consists of two steps: offline training and online testing. In the training stage, after extracting the keypoints for every training image using the Scale Invariance Feature Transform (SIFT), a vector quantization technique will map keypoints from every training image into a unified dimensional histogram vector (bag-of-words) after K-means clustering. This histogram is treated as an input vector for a multi-class SVM to build the classifier. In the testing stage, for every frame captured from a webcam, the hand is detected using my algorithm. Then, the keypoints are extracted for every small image that contains the detected hand posture and fed into the cluster model to map them into a bag-of-words vector, which is fed into the multi-class SVM classifier to recognize the hand gesture. Another hand gesture recognition system was proposed using Principle Components Analysis (PCA). The most eigenvectors and weights of training images are determined. In the testing stage, the hand posture is detected for every frame using my algorithm. Then, the small image that contains the detected hand is projected onto the most eigenvectors of training images to form its test weights. Finally, the minimum Euclidean distance is determined among the test weights and the training weights of each training image to recognize the hand gesture. Two application of gesture-based interaction with a 3D gaming virtual environment were implemented. The exertion videogame makes use of a stationary bicycle as one of the main inputs for game playing. The user can control and direct left-right movement and shooting actions in the game by a set of hand gesture commands, while in the second game, the user can control and direct a helicopter over the city by a set of hand gesture commands.

Image-based Gesture Recognition with Support Vector Machines

Author : Yu Yuan
Publisher : ProQuest
ISBN 13 : 9780549812494
Total Pages : pages
Book Rating : 4.8/5 (124 download)

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Book Synopsis Image-based Gesture Recognition with Support Vector Machines by : Yu Yuan

Download or read book Image-based Gesture Recognition with Support Vector Machines written by Yu Yuan and published by ProQuest. This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in various display and virtual technologies, coupled with an explosion in available computing power, have given rise to a number of novel human-computer interaction (HCI) modalities, among which gesture recognition is undoubtedly the most grammatically structured and complex. However, despite the abundance of novel interaction devices, the naturalness and efficiency of HCI has remained low. This is due in particular to the lack of robust sensory data interpretation techniques. To address the task of gesture recognition, this dissertation establishes novel probabilistic approaches based on support vector machines (SVM). Of special concern in this dissertation are the shapes of contact images on a multi-touch input device for both 2D and 3D. Five main topics are covered in this work. The first topic deals with the hand pose recognition problem. To perform classification of different gestures, a recognition system must attempt to leverage between class variations (semantically varying gestures), while accommodating potentially large within-class variations (different hand poses to perform certain gestures). For recognition of gestures, a sequence of hand shapes should be recognized. We present a novel shape recognition approach using Active Shape Model (ASM) based matching and SVM based classification. Firstly, a set of correspondences between the reference shape and query image are identified through ASM. Next, a dissimilarity measure is created to measure how well any correspondence in the set aligns the reference shape and candidate shape in the query image. Finally, SVM classification is employed to search through the set to find the best match from the kernel defined by the dissimilarity measure above. Results presented show better recognition results than conventional segmentation and template matching methods. In the second topic, dynamic time alignment (DTA) based SVM gesture recognition is addressed. In particular, the proposed method combines DTA and SVM by establishing a new kernel. The gesture data is first projected into a common eigenspace formed by principal component analysis (PCA) and a distance measure is derived from the DTA. By incorporating DTA in the kernel function, general classification problems with variable-sized sequential data can be handled. In the third topic, a C++ based gesture recognition application for the multi-touchpad is implemented. It uses the proposed gesture classification method along with a recursive neural networks approach to recognize definable gestures in real time, then runs an associated command. This application can further enable users with different disabilities or preferences to custom define gestures and enhance the functionality of the multi-touchpad. Fourthly, an SVM-based classification method that uses the DTW to measure the similarity score is presented. The key contribution of this approach is the extension of trajectory based approaches to handle shape information, thereby enabling the expansion of the system's gesture vocabulary. It consists of two steps: converting a given set of frames into fixed-length vectors and training an SVM from the vectorized manifolds. Using shape information not only yields discrimination among various gestures, but also enables gestures that cannot be characterized solely based on their motion information to be classified, thus boosting overall recognition scores. Finally, a computer vision based gesture command and communication system is developed. This system performs two major tasks: the first is to utilize the 3D traces of laser pointing devices as input to perform common keyboard and mouse control; the second is supplement free continuous gesture recognition, i.e., data gloves or other assistive devices are not necessary for 3D gestures recognition. As a result, the gesture can be used as a text entry system in wearable computers or mobile communication devices, though the recognition rate is lower than the approaches with the assistive tools. The purpose of this system is to develop new perceptual interfaces for human computer interaction based on visual input captured by computer vision systems, and to investigate how such interfaces can complement or replace traditional interfaces. Original contributions of this work span the areas of SVMs and interpretation of computer sensory inputs, such as gestures for advanced HCI. In particular, we have addressed the following important issues: (1) ASM base kernels for shape recognition. (2) DTA based sequence kernels for gesture classification. (3) Recurrent neural networks (RNN). (4) Exploration of a customizable HCI. (5) Computer vision based 3D gesture recognition algorithms and system.

Perception and Machine Intelligence

Author : Malay K. Kundu
Publisher : Springer
ISBN 13 : 3642273874
Total Pages : 394 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Perception and Machine Intelligence by : Malay K. Kundu

Download or read book Perception and Machine Intelligence written by Malay K. Kundu and published by Springer. This book was released on 2012-01-12 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the First Indo-Japanese conference on Perception and Machine Intelligence, PerMIn 2012, held in Kolkata, India, in January 2012. The 41 papers, presented together with 1 keynote paper and 3 plenary papers, were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections named perception; human-computer interaction; e-nose and e-tongue; machine intelligence and application; image and video processing; and speech and signal processing.

Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016)

Author : Ajith Abraham
Publisher : Springer
ISBN 13 : 3319606182
Total Pages : 753 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) by : Ajith Abraham

Download or read book Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) written by Ajith Abraham and published by Springer. This book was released on 2017-08-17 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents 70 carefully selected papers from a major joint event: the 8th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) and the 8th International Conference on Computational Aspects of Social Networks (CASoN 2016). SoCPaR–CASoN 2016, which was organized by the Machine Intelligence Research Labs (MIR Labs), USA and Vellore Institute of Technology (VIT), India and held at the VIT on December 19–21, 2016. It brings together researchers and practitioners from academia and industry to share their experiences and exchange new ideas on all interdisciplinary areas of soft computing and pattern recognition, as well as intelligent methods applied to social networks. This book is a valuable resource for practicing engineers/scientists and researchers working in the field of soft computing, pattern recognition and social networks.