Robust Template Update Strategy For Efficient Visual Object Tracking

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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.

Information Extraction and Object Tracking in Digital Video

Author :
Publisher : BoD – Books on Demand
ISBN 13 : 1839694602
Total Pages : 212 pages
Book Rating : 4.8/5 (396 download)

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Book Synopsis Information Extraction and Object Tracking in Digital Video by :

Download or read book Information Extraction and Object Tracking in Digital Video written by and published by BoD – Books on Demand. This book was released on 2022-08-17 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: The research on computer vision systems has been increasing every day and has led to the design of multiple types of these systems with innumerous applications in our daily life. The recent advances in artificial intelligence, together with the huge amount of digital visual data now available, have boosted vision system performance in several ways. Information extraction and visual object tracking are essential tasks in the field of computer vision with a huge number of real-world applications.This book is a result of research done by several researchers and professionals who have highly contributed to the field of image processing. It contains eight chapters divided into three sections. Section 1 consists of four chapters focusing on the problem of visual tracking. Section 2 includes three chapters focusing on information extraction from images. Finally, Section 3 includes one chapter that presents new advances in image sensors.

Computer Vision – ECCV 2020 Workshops

Author : Adrien Bartoli
Publisher : Springer Nature
ISBN 13 : 3030682382
Total Pages : 752 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Computer Vision – ECCV 2020 Workshops by : Adrien Bartoli

Download or read book Computer Vision – ECCV 2020 Workshops written by Adrien Bartoli and published by Springer Nature. This book was released on 2021-01-30 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 6-volume set, comprising the LNCS books 12535 until 12540, constitutes the refereed proceedings of 28 out of the 45 workshops held at the 16th European Conference on Computer Vision, ECCV 2020. The conference was planned to take place in Glasgow, UK, during August 23-28, 2020, but changed to a virtual format due to the COVID-19 pandemic. The 249 full papers, 18 short papers, and 21 further contributions included in the workshop proceedings were carefully reviewed and selected from a total of 467 submissions. The papers deal with diverse computer vision topics. Part V includes: The 16th Embedded Vision Workshop; Real-World Computer Vision from Inputs with Limited Quality (RLQ); The Bright and Dark Sides of Computer Vision: Challenges and Opportunities for Privacy and Security (CV-COPS 2020); The Visual Object Tracking Challenge Workshop (VOT 2020); and Video Turing Test: Toward Human-Level Video Story Understanding.

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 and Accurate Generic Visual Object Tracking Using Deep Neural Networks in Unconstrained Environments

Author : Javad Khaghani
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (135 download)

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Book Synopsis Robust and Accurate Generic Visual Object Tracking Using Deep Neural Networks in Unconstrained Environments by : Javad Khaghani

Download or read book Robust and Accurate Generic Visual Object Tracking Using Deep Neural Networks in Unconstrained Environments written by Javad Khaghani and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The availability of affordable cameras and video-sharing platforms have provided a massive amount of low-cost videos. Automatic tracking of objects of interest in these videos is the essential step for complex visual analyses. As a fundamental computer vision task, Visual Object Tracking aims at accurately (and efficiently) locating a target in an arbitrary video, given an initial bounding box in the first frame. While the state-of-the-art deep trackers provide promising results, they still suffer from performance degradation in challenging scenarios including small targets, occlusion, and viewpoint change. Also, estimating the axis-aligned bounding box enclosing the target cannot provide the full details about its boundaries. Moreover, the performance of tracker relies on its well-crafted modules, typically consisting of manually-designed network architectures to boost the performance. In this thesis, first, a context-aware IoU-guided tracker is proposed that exploits a multitask two-stream network and an offline reference proposal generation strategy to improve the accuracy for tracking class-agnostic small objects from aerial videos of medium to high altitudes. Then, a two-stage segmentation tracker to provide better semantically interpretation of target in videos is developed. Finally, a novel cell-level differentiable architecture search with early stopping is introduced into Siamese tracking framework to automate the network design of the tracking module, aiming to adapt backbone features to the objective of network. Extensive experimental evaluations on widely used generic and aerial visual tracking benchmarks demonstrate the effectiveness of the proposed methods.

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.

Robust Appearance Based Modelling for Effective Visual Object Tracking

Author : Mark David Jenkins
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (16 download)

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Book Synopsis Robust Appearance Based Modelling for Effective Visual Object Tracking by : Mark David Jenkins

Download or read book Robust Appearance Based Modelling for Effective Visual Object Tracking written by Mark David Jenkins and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Online Visual Tracking

Author : Huchuan Lu
Publisher : Springer
ISBN 13 : 9811304696
Total Pages : 128 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Online Visual Tracking by : Huchuan Lu

Download or read book Online Visual Tracking written by Huchuan Lu and published by Springer. This book was released on 2019-05-30 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state of the art in online visual tracking, including the motivations, practical algorithms, and experimental evaluations. Visual tracking remains a highly active area of research in Computer Vision and the performance under complex scenarios has substantially improved, driven by the high demand in connection with real-world applications and the recent advances in machine learning. A large variety of new algorithms have been proposed in the literature over the last two decades, with mixed success. Chapters 1 to 6 introduce readers to tracking methods based on online learning algorithms, including sparse representation, dictionary learning, hashing codes, local model, and model fusion. In Chapter 7, visual tracking is formulated as a foreground/background segmentation problem, and tracking methods based on superpixels and end-to-end deep networks are presented. In turn, Chapters 8 and 9 introduce the cutting-edge tracking methods based on correlation filter and deep learning. Chapter 10 summarizes the book and points out potential future research directions for visual tracking. The book is self-contained and suited for all researchers, professionals and postgraduate students working in the fields of computer vision, pattern recognition, and machine learning. It will help these readers grasp the insights provided by cutting-edge research, and benefit from the practical techniques available for designing effective visual tracking algorithms. Further, the source codes or results of most algorithms in the book are provided at an accompanying website.

Template Matching Techniques in Computer Vision

Author : Roberto Brunelli
Publisher : John Wiley & Sons
ISBN 13 : 9780470744048
Total Pages : 348 pages
Book Rating : 4.7/5 (44 download)

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Book Synopsis Template Matching Techniques in Computer Vision by : Roberto Brunelli

Download or read book Template Matching Techniques in Computer Vision written by Roberto Brunelli and published by John Wiley & Sons. This book was released on 2009-04-29 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: The detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems. This book and the accompanying website, focus on template matching, a subset of object recognition techniques of wide applicability, which has proved to be particularly effective for face recognition applications. Using examples from face processing tasks throughout the book to illustrate more general object recognition approaches, Roberto Brunelli: examines the basics of digital image formation, highlighting points critical to the task of template matching; presents basic and advanced template matching techniques, targeting grey-level images, shapes and point sets; discusses recent pattern classification paradigms from a template matching perspective; illustrates the development of a real face recognition system; explores the use of advanced computer graphics techniques in the development of computer vision algorithms. Template Matching Techniques in Computer Vision is primarily aimed at practitioners working on the development of systems for effective object recognition such as biometrics, robot navigation, multimedia retrieval and landmark detection. It is also of interest to graduate students undertaking studies in these areas.

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.

A New Visual Tracking Algorithm Based on Template Registration for Accurate Object Tracking

Author : Zhang, Xi
Publisher :
ISBN 13 :
Total Pages : 60 pages
Book Rating : 4.:/5 (956 download)

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Book Synopsis A New Visual Tracking Algorithm Based on Template Registration for Accurate Object Tracking by : Zhang, Xi

Download or read book A New Visual Tracking Algorithm Based on Template Registration for Accurate Object Tracking written by Zhang, Xi and published by . This book was released on 2015 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual tracking serves an important role in a wide variety of applications like video surveillance, robotic manipulation and augmented reality. The goal of tracking in the last two cases here is to efficiently and accurately locate the object in each frame of an image sequence/stream, with the target selected in the first frame. Various visual tracking algorithms have been proposed in literature recently, but many of them fall in the category of long-term object tracking algorithms that are more focused on the tracking robustness and are not accurate enough for such applications. On the other hand, registration based tracking algorithms can achieve greater accuracy in tracking high degree-of-freedom (DOF) object motion, but are likely to fail when fast object motion or noise in the image space is present. In this thesis, we focus on improving the robustness of registration based tracking algorithms towards fast motion and noise, while retaining good accuracy and efficiency. Concretely, we propose a novel tracking algorithm called RKLT that takes advantage of both 2D KLT trackers and the RANSAC algorithm for robust 8 DOF inter-frame target motion estimation. Inlier pixels selected by RANSAC are used to perform global registration using the efficient Inverse Compositional (IC) tracker to avoid tracking drift. In addition, we also explore the different parameterizations on the state space model of a registration based tracker which characterizes the object state in 2D image space during tracking. In particular, we show how the corner based parameterization can be applied to the 8 DOF tracker using efficient second-order minimization (ESM). The impact of different parameterizations on the performance of IC and ESM trackers is also investigated in the experiments. Finally, we introduce a new tracking dataset, Tracking for Manipulation Tasks (TMT) dataset with over 100 image sequences. New evaluation methods are also designed for better evaluation of high DOF trackers with greater accuracy. A tracking testbed is also provided for more convenient comparison among different tracking algorithms. In the experiments, the proposed RKLT algorithm performs better than three other registration based trackers, especially in the faster sequences of TMT dataset. In the public Metaio benchmark too, RKLT achieves better results than the ESM tracker which is considered the state-of-the-art.

Robust Structured Tracking

Author : Ivan Bogun
Publisher :
ISBN 13 :
Total Pages : 212 pages
Book Rating : 4.:/5 (962 download)

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Book Synopsis Robust Structured Tracking by : Ivan Bogun

Download or read book Robust Structured Tracking written by Ivan Bogun and published by . This book was released on 2016 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model-free visual tracking is an important problem in computer vision. The abundance of applications make the problem attractive, and, as a result, significant progress was made, especially in the recent years. A number of reasons make tracking a hard problem: change of lighting conditions throughout the video, change of scale and rotation of the object, as well as frequent occlusions. In this dissertation, we build upon a tracker known as Struck, which is based on a structured support vector machine. To make the structured tracker robust, we improve it in a number of ways. To make the structured tracker robust to short-time occlusions and false-positive detections, we propose to use the Robust Kalman filter. Here, we develop a strategy that allows us to detect, and recover from, short-time occlusions and/or incorrect detections. By treating inconsistent detections, which are labeled by the filter as outliers, we show that our new method, called RobStruck, improves the tracking accuracy as measured by standard tracking-accuracy metrics. To guide the tracker into locations that are more likely to contain an object, we propose to use saliency measures. Saliency measures, also known as objectness, estimate how likely a given location in the image to contain an object of any type. The objectness measures we consider here - straddling and edge density - are based on semantic object segmentation and edge detection. These measures are unsupervised, and are fast to compute - an ideal fit for tracking, where real-time performance is often desired. We build a object-aware tracker, which we call ObjStruck and show that objectness measures improve tracking. To find a better feature representation, we incorporate deep features from pre-learned deep-convolutional network in a computationally-efficient manner. Using a M-Best diverse-sampling approach, we can sample a small and diverse set of bounding boxes that are likely to contain the target. These bounding boxes are then used to perform detection using deep features. The resulting tracker, which we call MBestStruck, uses high-quality feature representation while remaining computationally efficient. We systematically evaluate each of our contributions on four different visual-tracking benchmarks and compare them to the state-of-the-art.

Advanced Concepts for Intelligent Vision Systems

Author : Wilfried Philips
Publisher : Springer
ISBN 13 : 354044632X
Total Pages : 1246 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Advanced Concepts for Intelligent Vision Systems by : Wilfried Philips

Download or read book Advanced Concepts for Intelligent Vision Systems written by Wilfried Philips and published by Springer. This book was released on 2006-10-04 with total page 1246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2006. The book presents 45 revised full papers and 65 revised poster papers. Topical sections include noise reduction and restoration, segmentation, motion estimation and tracking, video processing and coding, camera calibration, image registration and stereo matching, biometrics and security, medical imaging, image retrieval and image understanding, and more.

Image and Vision Computing

Author : Wei Qi Yan
Publisher : Springer Nature
ISBN 13 : 3031258258
Total Pages : 537 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Image and Vision Computing by : Wei Qi Yan

Download or read book Image and Vision Computing written by Wei Qi Yan and published by Springer Nature. This book was released on 2023-02-03 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 37th International Conference, IVCNZ 2022, which took place in Auckland, New Zealand, in November 2022. The 37 papers (14 accepted for long oral presentation, 23 for short oral presentation) included in this volume were carefully reviewed and selected from 79 submissions. The conference presents papers on all aspects of computer vision, image processing, computer graphics, virtual and augmented reality, visualization, and HCI applications related to these fields.

Computer Vision – ECCV 2018 Workshops

Author : Laura Leal-Taixé
Publisher : Springer
ISBN 13 : 3030110095
Total Pages : 750 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Computer Vision – ECCV 2018 Workshops by : Laura Leal-Taixé

Download or read book Computer Vision – ECCV 2018 Workshops written by Laura Leal-Taixé and published by Springer. This book was released on 2019-01-22 with total page 750 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set comprising the LNCS volumes 11129-11134 constitutes the refereed proceedings of the workshops that took place in conjunction with the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.43 workshops from 74 workshops proposals were selected for inclusion in the proceedings. The workshop topics present a good orchestration of new trends and traditional issues, built bridges into neighboring fields, and discuss fundamental technologies and novel applications.

Pattern Recognition and Computer Vision

Author : Huimin Ma
Publisher : Springer Nature
ISBN 13 : 3030880044
Total Pages : 634 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Pattern Recognition and Computer Vision by : Huimin Ma

Download or read book Pattern Recognition and Computer Vision written by Huimin Ma and published by Springer Nature. This book was released on 2021-10-22 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 4-volume set LNCS 13019, 13020, 13021 and 13022 constitutes the refereed proceedings of the 4th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2021, held in Beijing, China, in October-November 2021. The 201 full papers presented were carefully reviewed and selected from 513 submissions. The papers have been organized in the following topical sections: Object Detection, Tracking and Recognition; Computer Vision, Theories and Applications, Multimedia Processing and Analysis; Low-level Vision and Image Processing; Biomedical Image Processing and Analysis; Machine Learning, Neural Network and Deep Learning, and New Advances in Visual Perception and Understanding.

Computer Vision – ECCV 2018

Author : Vittorio Ferrari
Publisher : Springer
ISBN 13 : 3030012409
Total Pages : 860 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Computer Vision – ECCV 2018 by : Vittorio Ferrari

Download or read book Computer Vision – ECCV 2018 written by Vittorio Ferrari and published by Springer. This book was released on 2018-10-06 with total page 860 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.