A Hybrid Model Approach For Real Time Visual Object Tracking

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A Hybrid Model Approach for Real-time Visual Object Tracking

Author : Jinwei Yuan
Publisher :
ISBN 13 :
Total Pages : 194 pages
Book Rating : 4.:/5 (97 download)

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Book Synopsis A Hybrid Model Approach for Real-time Visual Object Tracking by : Jinwei Yuan

Download or read book A Hybrid Model Approach for Real-time Visual Object Tracking written by Jinwei Yuan and published by . This book was released on 2016 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tracking an unknown general object in video sequences is a challenging task in many computer vision applications since the appearance of the object can change significantly due to pose variations, illumination changes, shape deformations, and abrupt motions. In this dissertation, we address these object tracking challenges by building a hybrid model tracker which consists of a tracking by detection framework and a Kalman filtering framework. We first present two tracking by detection approaches by applying the naive Bayes classifier and the support vector machine approach respectively. In both approaches, effective feature selection schemes are proposed to select the most informative features to construct a robust appearance model. Then, we propose a novel approach for appearance estimation in object tracking. Most existing tracking algorithms assume that the object appearance is static for two consecutive frames, which remains a potential risk causing the drift problem. We build a Kalman filtering framework to generate a statistically optimal estimation for the object appearance. The proposed method greatly reduces the error between the true object appearance and the estimated object appearance, thus effectively improving the tracking performance. Finally, we develop and implement a hybrid model tracking system which combines the discriminative model constructed in the tracking by detection framework and the generative model estimated by the Kalman filtering framework. The support vector machine tracker is applied to provide accurate feedback to the Kalman filtering framework, which improves the estimating precision. The Kalman filtering framework then generates the optimal estimation of the object appearance and determines the object location by the best fitting with the appearance model. The object location determined by maximizing the classifier confidence in the support vector tracking framework is finally corrected by the Kalman filtering framework. Therefore, the proposed tracking system provides more meaningful tracking results compared with traditional tracking by detection algorithms which suffer from the inconsistent objectives between tracking and classification. Our experimental evaluations show that a significant improvement over state-of-the-art methods is achieved by our approach.

Visual Object Tracking from Correlation Filter to Deep Learning

Author : Weiwei Xing
Publisher : Springer Nature
ISBN 13 : 9811662428
Total Pages : 202 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Visual Object Tracking from Correlation Filter to Deep Learning by : Weiwei Xing

Download or read book Visual Object Tracking from Correlation Filter to Deep Learning written by Weiwei Xing and published by Springer Nature. This book was released on 2021-11-18 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book focuses on visual object tracking systems and approaches based on correlation filter and deep learning. Both foundations and implementations have been addressed. The algorithm, system design and performance evaluation have been explored for three kinds of tracking methods including correlation filter based methods, correlation filter with deep feature based methods, and deep learning based methods. Firstly, context aware and multi-scale strategy are presented in correlation filter based trackers; then, long-short term correlation filter, context aware correlation filter and auxiliary relocation in SiamFC framework are proposed for combining correlation filter and deep learning in visual object tracking; finally, improvements in deep learning based trackers including Siamese network, GAN and reinforcement learning are designed. The goal of this book is to bring, in a timely fashion, the latest advances and developments in visual object tracking, especially correlation filter and deep learning based methods, which is particularly suited for readers who are interested in the research and technology innovation in visual object tracking and related fields.

Visual Object Tracking with Deep Neural Networks

Author : Pier Luigi Mazzeo
Publisher : BoD – Books on Demand
ISBN 13 : 1789851572
Total Pages : 208 pages
Book Rating : 4.7/5 (898 download)

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Book Synopsis Visual Object Tracking with Deep Neural Networks by : Pier Luigi Mazzeo

Download or read book Visual Object Tracking with Deep Neural Networks written by Pier Luigi Mazzeo and published by BoD – Books on Demand. This book was released on 2019-12-18 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual object tracking (VOT) and face recognition (FR) are essential tasks in computer vision with various real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. This book presents the state-of-the-art and new algorithms, methods, and systems of these research fields by using deep learning. It is organized into nine chapters across three sections. Section I discusses object detection and tracking ideas and algorithms; Section II examines applications based on re-identification challenges; and Section III presents applications based on FR research.

Visual Object Tracking using Deep Learning

Author : Ashish Kumar
Publisher : CRC Press
ISBN 13 : 1000991008
Total Pages : 248 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Visual Object Tracking using Deep Learning by : Ashish Kumar

Download or read book Visual Object Tracking using Deep Learning written by Ashish Kumar and published by CRC Press. This book was released on 2023-11-10 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. The book also: Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methods. Elaborates on the salient features of deep learning trackers along with traditional trackers, wherein the handcrafted features are fused to reduce computational complexity. Illustrates various categories of correlation filter-based trackers suitable for superior and efficient performance under tedious tracking scenarios. Explores the future research directions for visual tracking by analyzing the real-time applications. The book comprehensively discusses various deep learning-based tracking architectures along with conventional tracking methods. It covers in-depth analysis of various feature extraction techniques, evaluation metrics and benchmark available for performance evaluation of tracking frameworks. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

Object Tracking Technology

Author : Ashish Kumar
Publisher : Springer Nature
ISBN 13 : 9819932882
Total Pages : 280 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Object Tracking Technology by : Ashish Kumar

Download or read book Object Tracking Technology written by Ashish Kumar and published by Springer Nature. This book was released on 2023-10-27 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increase in urban population, it became necessary to keep track of the object of interest. In favor of SDGs for sustainable smart city, with the advancement in technology visual tracking extends to track multi-target present in the scene rather estimating location for single target only. In contrast to single object tracking, multi-target introduces one extra step of detection. Tracking multi-target includes detecting and categorizing the target into multiple classes in the first frame and provides each individual target an ID to keep its track in the subsequent frames of a video stream. One category of multi-target algorithms exploits global information to track the target of the detected target. On the other hand, some algorithms consider present and past information of the target to provide efficient tracking solutions. Apart from these, deep leaning-based algorithms provide reliable and accurate solutions. But, these algorithms are computationally slow when applied in real-time. This book presents and summarizes the various visual tracking algorithms and challenges in the domain. The various feature that can be extracted from the target and target saliency prediction is also covered. It explores a comprehensive analysis of the evolution from traditional methods to deep learning methods, from single object tracking to multi-target tracking. In addition, the application of visual tracking and the future of visual tracking can also be introduced to provide the future aspects in the domain to the reader. This book also discusses the advancement in the area with critical performance analysis of each proposed algorithm. This book will be formulated with intent to uncover the challenges and possibilities of efficient and effective tracking of single or multi-object, addressing the various environmental and hardware challenges. The intended audience includes academicians, engineers, postgraduate students, developers, professionals, military personals, scientists, data analysts, practitioners, and people who are interested in exploring more about tracking.· Another projected audience are the researchers and academicians who identify and develop methodologies, frameworks, tools, and applications through reference citations, literature reviews, quantitative/qualitative results, and discussions.

Model-based Visual Tracking

Author : Giorgio Panin
Publisher : John Wiley & Sons
ISBN 13 : 111800213X
Total Pages : 251 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis Model-based Visual Tracking by : Giorgio Panin

Download or read book Model-based Visual Tracking written by Giorgio Panin and published by John Wiley & Sons. This book was released on 2011-04-12 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has two main goals: to provide a unifed and structured overview of this growing field, as well as to propose a corresponding software framework, the OpenTL library, developed by the author and his working group at TUM-Informatik. The main objective of this work is to show, how most real-world application scenarios can be naturally cast into a common description vocabulary, and therefore implemented and tested in a fully modular and scalable way, through the defnition of a layered, object-oriented software architecture.The resulting architecture covers in a seamless way all processing levels, from raw data acquisition up to model-based object detection and sequential localization, and defines, at the application level, what we call the tracking pipeline. Within this framework, extensive use of graphics hardware (GPU computing) as well as distributed processing, allows real-time performances for complex models and sensory systems.

Visual Object Tracking using Deep Learning

Author : Ashish Kumar
Publisher : CRC Press
ISBN 13 : 1000990982
Total Pages : 216 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Visual Object Tracking using Deep Learning by : Ashish Kumar

Download or read book Visual Object Tracking using Deep Learning written by Ashish Kumar and published by CRC Press. This book was released on 2023-11-20 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. The book also: Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methods Elaborates on the salient features of deep learning trackers along with traditional trackers, wherein the handcrafted features are fused to reduce computational complexity Illustrates various categories of correlation filter-based trackers suitable for superior and efficient performance under tedious tracking scenarios Explores the future research directions for visual tracking by analyzing the real-time applications The book comprehensively discusses various deep learning-based tracking architectures along with conventional tracking methods. It covers in-depth analysis of various feature extraction techniques, evaluation metrics and benchmark available for performance evaluation of tracking frameworks. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

Robust Template Update Strategy for Efficient Visual Object Tracking

Author : Awet Haileslassie Gebrehiwot
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)

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Book Synopsis Robust Template Update Strategy for Efficient Visual Object Tracking by : Awet Haileslassie Gebrehiwot

Download or read book Robust Template Update Strategy for Efficient Visual Object Tracking written by Awet Haileslassie Gebrehiwot and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-time visual object tracking is an open problem in computer vision, with multiple applications in the industry, such as autonomous vehicles, human-machine interaction, intelligent cinematography, automated surveillance, and autonomous social navigation. The challenge of tracking a target of interest is critical to all of these applications. Recently, tracking algorithms that use siamese neural networks trained offline on large-scale datasets of image pairs have achieved the best performance exceeding real-time speed on multiple benchmarks. Results show that siamese approaches can be applied to enhance the tracking capabilities by learning deeper features of the object,Äôs appearance. SiamMask utilized the power of siamese networks and supervised learning approaches to solve the problem of arbitrary object tracking in real-time speed. However, its practical applications are limited due to failures encountered during testing. In order to improve the robustness of the tracker and make it applicable for the intended real-world application, two improvements have been incorporated, each addressing a different aspect of the tracking task. The first one is a data augmentation strategy to consider both motion-blur and low-resolution during training. It aims to increase the robustness of the tracker against a motion-blurred and low-resolution frames during inference. The second improvement is a target template update strategy that utilizes both the initial ground truth template and a supplementary updatable template, which considers the score of the predicted target for an efficient template update strategy by avoiding template updates during severe occlusion. All of the improvements were extensively evaluated and have achieved state-of-the-art performance in the VOT2018 and VOT2019 benchmarks. Our method (VPU-SiamM) has been submitted to the VOT-ST 2020 challenge, and it is ranked 16th out of 38 submitted tracking methods according to the Expected average overlap (EAO) metrics. VPU_SiamM Implementation can be found from the VOT2020 Trackers repository1.

Hybrid Intelligence for Image Analysis and Understanding

Author : Siddhartha Bhattacharyya
Publisher : John Wiley & Sons
ISBN 13 : 1119242932
Total Pages : 467 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Hybrid Intelligence for Image Analysis and Understanding by : Siddhartha Bhattacharyya

Download or read book Hybrid Intelligence for Image Analysis and Understanding written by Siddhartha Bhattacharyya and published by John Wiley & Sons. This book was released on 2017-07-27 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: A synergy of techniques on hybrid intelligence for real-life image analysis Hybrid Intelligence for Image Analysis and Understanding brings together research on the latest results and progress in the development of hybrid intelligent techniques for faithful image analysis and understanding. As such, the focus is on the methods of computational intelligence, with an emphasis on hybrid intelligent methods applied to image analysis and understanding. The book offers a diverse range of hybrid intelligence techniques under the umbrellas of image thresholding, image segmentation, image analysis and video analysis. Key features: Provides in-depth analysis of hybrid intelligent paradigms. Divided into self-contained chapters. Provides ample case studies, illustrations and photographs of real-life examples to illustrate findings and applications of different hybrid intelligent paradigms. Offers new solutions to recent problems in computer science, specifically in the application of hybrid intelligent techniques for image analysis and understanding, using well-known contemporary algorithms. The book is essential reading for lecturers, researchers and graduate students in electrical engineering and computer science.

Moving Objects Detection Using Machine Learning

Author : Navneet Ghedia
Publisher : Springer Nature
ISBN 13 : 3030909107
Total Pages : 91 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Moving Objects Detection Using Machine Learning by : Navneet Ghedia

Download or read book Moving Objects Detection Using Machine Learning written by Navneet Ghedia and published by Springer Nature. This book was released on 2022-01-01 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows how machine learning can detect moving objects in a digital video stream. The authors present different background subtraction approaches, foreground segmentation, and object tracking approaches to accomplish this. They also propose an algorithm that considers a multimodal background subtraction approach that can handle a dynamic background and different constraints. The authors show how the proposed algorithm is able to detect and track 2D & 3D objects in monocular sequences for both indoor and outdoor surveillance environments and at the same time, also able to work satisfactorily in a dynamic background and with challenging constraints. In addition, the shows how the proposed algorithm makes use of parameter optimization and adaptive threshold techniques as intrinsic improvements of the Gaussian Mixture Model. The presented system in the book is also able to handle partial occlusion during object detection and tracking. All the presented work and evaluations were carried out in offline processing with the computation done by a single laptop computer with MATLAB serving as software environment.

Computer Vision and Computer Graphics. Theory and Applications

Author : José Braz
Publisher : Springer Science & Business Media
ISBN 13 : 3540896821
Total Pages : 258 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Computer Vision and Computer Graphics. Theory and Applications by : José Braz

Download or read book Computer Vision and Computer Graphics. Theory and Applications written by José Braz and published by Springer Science & Business Media. This book was released on 2008-12-05 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers from VISIGRAPP 2007, the Joint Conference on Computer Vision and Computer Graphics, comprising two component conferences, namely, the International Conference on Computer Vision Theory and Applications (VISAPP) and the International Conference on Computer Graphics Theory and App- cations (GRAPP), held in Barcelona, Spain, during March 8–11, 2007. We received quite a high number of paper submissions: 382 in total for both conf- ences. We had contributions from more than 50 countries in all five continents. This confirms the success and global dimension of these jointly organized conferences. After a rigorous double-blind evaluation method, a total of 78 submissions were accepted as full papers. From those, 18 got selected for inclusion in this book. To ensure the sci- tific quality of the contributions, these were selected from papers that were evaluated with the highest scores by the VISIGRAPP Program Committee members and then they were extended and revised by the authors. Special thanks go to all contributors and re- rees, without whom this book would not have been possible. VISIGRAPP 2007 included four invited keynote lectures, presented by internati- ally recognized researchers. The presentations represented an important contribution to increasing the overall quality of the conference. We would like to express our - preciation to all invited keynote speakers, in alphabetical order: Jake K. Aggarwal (The University of Texas at Austin/USA), André Gagalowicz (INRIA/France), Wo- gang Heidrich (University of British Columbia/Canada), Mel Slater (Universitat Politècnica de Catalunya/Spain).

Artificial Intelligence for Smart Healthcare

Author : Parul Agarwal
Publisher : Springer Nature
ISBN 13 : 3031236025
Total Pages : 527 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Artificial Intelligence for Smart Healthcare by : Parul Agarwal

Download or read book Artificial Intelligence for Smart Healthcare written by Parul Agarwal and published by Springer Nature. This book was released on 2023-06-09 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides information on interdependencies of medicine and telecommunications engineering and how the two must rely on each other to effectively function in this era. The book discusses new techniques for medical service improvisation such as clear-cut views on medical technologies. The authors provide chapters on communication essentiality in healthcare, processing of medical amenities using medical images, the importance of data and information technology in medicine, and machine learning and artificial intelligence in healthcare. Authors include researchers, academics, and professionals in the field.

Deep Learning in Internet of Things for Next Generation Healthcare

Author : Lavanya Sharma
Publisher : CRC Press
ISBN 13 : 1040030823
Total Pages : 311 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Deep Learning in Internet of Things for Next Generation Healthcare by : Lavanya Sharma

Download or read book Deep Learning in Internet of Things for Next Generation Healthcare written by Lavanya Sharma and published by CRC Press. This book was released on 2024-06-18 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest developments in deep learning-enabled healthcare tools and technologies and offers practical ideas for using the IoT with deep learning (motion-based object data) to deal with human dynamics and challenges including critical application domains, technologies, medical imaging, drug discovery, insurance fraud detection and solutions to handle relevant challenges. This book covers real-time healthcare applications, novel solutions, current open challenges, and the future of deep learning for next-generation healthcare. It includes detailed analysis of the utilization of the IoT with deep learning and its underlying technologies in critical application areas of emergency departments such as drug discovery, medical imaging, fraud detection, Alzheimer's disease, and genomes. Presents practical approaches of using the IoT with deep learning vision and how it deals with human dynamics Offers novel solution for medical imaging including skin lesion detection, cancer detection, enhancement techniques for MRI images, automated disease prediction, fraud detection, genomes, and many more Includes the latest technological advances in the IoT and deep learning with their implementations in healthcare Combines deep learning and analysis in the unified framework to understand both IoT and deep learning applications Covers the challenging issues related to data collection by sensors, detection and tracking of moving objects and solutions to handle relevant challenges Postgraduate students and researchers in the departments of computer science, working in the areas of the IoT, deep learning, machine learning, image processing, big data, cloud computing, and remote sensing will find this book useful.

Scientific and Technical Aerospace Reports

Author :
Publisher :
ISBN 13 :
Total Pages : 836 pages
Book Rating : 4.:/5 (31 download)

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Book Synopsis Scientific and Technical Aerospace Reports by :

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1994 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Image Analysis and Processing — ICIAP 2015

Author : Vittorio Murino
Publisher : Springer
ISBN 13 : 3319232312
Total Pages : 739 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Image Analysis and Processing — ICIAP 2015 by : Vittorio Murino

Download or read book Image Analysis and Processing — ICIAP 2015 written by Vittorio Murino and published by Springer. This book was released on 2015-08-20 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 9279 and 9280 constitutes the refereed proceedings of the 18th International Conference on Image Analysis and Processing, ICIAP 2015, held in Genoa, Italy, in September 2015. The 129 papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in the following seven topical sections: video analysis and understanding, multiview geometry and 3D computer vision, pattern recognition and machine learning, image analysis, detection and recognition, shape analysis and modeling, multimedia, and biomedical applications.

Computer Vision and Image Processing

Author : Balasubramanian Raman
Publisher : Springer Nature
ISBN 13 : 3031113462
Total Pages : 616 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Computer Vision and Image Processing by : Balasubramanian Raman

Download or read book Computer Vision and Image Processing written by Balasubramanian Raman and published by Springer Nature. This book was released on 2022-07-23 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set (CCIS 1567-1568) constitutes the refereed proceedings of the 6h International Conference on Computer Vision and Image Processing, CVIP 2021, held in Rupnagar, India, in December 2021. The 70 full papers and 20 short papers were carefully reviewed and selected from the 260 submissions. The papers present recent research on such topics as biometrics, forensics, content protection, image enhancement/super-resolution/restoration, motion and tracking, image or video retrieval, image, image/video processing for autonomous vehicles, video scene understanding, human-computer interaction, document image analysis, face, iris, emotion, sign language and gesture recognition, 3D image/video processing, action and event detection/recognition, medical image and video analysis, vision-based human GAIT analysis, remote sensing, and more.

Computer Vision, Pattern Recognition, Image Processing, and Graphics

Author : R. Venkatesh Babu
Publisher : Springer Nature
ISBN 13 : 9811586977
Total Pages : 642 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Computer Vision, Pattern Recognition, Image Processing, and Graphics by : R. Venkatesh Babu

Download or read book Computer Vision, Pattern Recognition, Image Processing, and Graphics written by R. Venkatesh Babu and published by Springer Nature. This book was released on 2020-11-16 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th National Conference on Computer Vision, Pattern Recognition, Image Processing, and Graphics, NCVPRIPG 2019, held in Hubballi, India, in December 2019. The 55 revised full papers 3 short papers presented in this volume were carefully reviewed and selected from 210 submissions. The papers are organized in topical sections on vision and geometry, learning and vision, image processing and document analysis, detection and recognition.