Visual Object Tracking In Dynamic Scenes
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Visual Object Tracking In Dynamic Scenes
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Author : Mohamed Hamed Abdelpakey
language : en
Publisher:
Release Date : 2021
Visual Object Tracking In Dynamic Scenes written by Mohamed Hamed Abdelpakey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Visual object tracking is a fundamental task in the field computer vision. Visual object tracking is widely used in numerous applications which include, but are not limited to video surveillance, image understanding, robotics, and human-computer interaction. In essence, visual object tracking is the problem of estimating the states/trajectory of the object of interest over time. Unlike other tasks such as object detection where the number of classes/categories are defined beforehand, the only available information of the object of interest is at the first frame. Even though, Deep Learning (DL) has revolutionised most computer vision tasks, visual object tracking still imposes several challenges. The nature of visual object tracking task is stochastic, where no prior-knowledge is available about the object of interest during the training or testing/inference. Moreover, visual object tracking is a class-agnostic task, as opposed object detection and segmentation tasks. In this thesis, the main objective is to develop and advance the visual object trackers using novel designs of deep learning frameworks and mathematical formulations. To take advantage of different trackers, a novel framework is developed to track moving objects based on a composite framework and a reporter mechanism. The composite framework has built-in trackers and user-defined trackers to track the object of interest. The framework contains a module to calculate the robustness for each tracker and a reporter mechanism serves as a recovery mechanism if trackers fail to locate the object of interest. Different trackers may fail to track the object of interest, thus, a more robust framework based on Siamese network architecture, namely DensSiam, is proposed to use the concept of dense layers and connects each dense layer in the network to all layers in a feed-forward fashion with a similarity-learning function. DensSiam also includes a Self-Attention mechanism to force the network to pay more attention to non-local features during offline training. Generally, Siamese trackers do not fully utilize semantic and objectness information from pre-trained networks that have been trained on an image classification task. To solve this problem a novel architecture design is proposed , dubbed DomainSiam, to learn a Domain-Aware that fully utilizes semantic and objectness information while producing a class-agnostic track using a ridge regression network. Moreover, to reduce the sparsity problem, we solve the ridge regression problem with a differentiable weighted-dynamic loss function. Siamese trackers have high speed and work in real-time, however, they lack high accuracy. To overcome this challenge, a novel dynamic policy gradient Agent-Environment architecture with Siamese network (DP-Siam) is proposed to train the tracker to increase the accuracy and the expected average overlap while running in real-time. DP-Siam is trained offline with reinforcement learning to produce a continuous action that predicts the optimal object location. One of the common design block in most object trackers in the literature is the backbone network, where the backbone network is trained in the feature space. To design a backbone network that maps from feature space to another space (i.e., joint-nullspace) and more suitable for object tracking and classification, a novel framework is proposed. The new framework is called NullSpaceNet has a clear interpretation for the feature representation and the features in this space are more separable. NullSpaceNet is utilized in object tracking by regularizing the discriminative joint-nullspace backbone network. The novel tracker is called NullSpaceRDAR, and encourages the network to have a representation for the target-specific information for the object of interest in the joint-nullspace. In contrast to feature space where objects from a specific class are categorized into one category however, it is insensitive to intra-class variations. Furthermore, we use the NullSpaceNet backbone to learn a tracker, dubbed NullSpaceRDAR, with a regularized discriminative joint-nullspace backbone network that is specifically designed for object tracking. In the regularized discriminative joint-nullspace, the features from the same target-specific are collapsed into one point in the joint-null space and different targetspecific features are collapsed into different points in the joint-nullspace. Consequently, the joint-nullspace forces the network to be sensitive to the variations of the object from the same class (intra-class variations). Moreover, a dynamic adaptive loss function is proposed to select the suitable loss function from a super-set family of losses based on the training data to make NullSpaceRDAR more robust to different challenges.
Visual Object Tracking
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Author : Xin Zhao
language : en
Publisher: Springer Nature
Release Date : 2025-07-01
Visual Object Tracking written by Xin Zhao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Computers categories.
This book delves into visual object tracking (VOT), a fundamental aspect of computer vision crucial for replicating human dynamic vision, with applications ranging from self-driving vehicles to surveillance systems. Despite significant strides propelled by deep learning, challenges such as target deformation and motion persist, exposing a disparity between cutting-edge VOT systems and human performance. This observation underscores the necessity to thoroughly scrutinize and enhance evaluation methodologies within VOT research. Hence, the primary objective of this book is to equip readers with essential insights into dynamic visual tasks encapsulated by VOT. Beginning with the elucidation of task definitions, it integrates interdisciplinary perspectives on evaluation techniques. The book is organized into five parts, tracing the evolution of VOT from perceptual to cognitive intelligence, exploring the experimental frameworks utilized in assessments, analyzing the various agents involved, including tracking algorithms and human visual tracking, and dissecting evaluation mechanisms through both machine–machine and human–machine comparisons. Furthermore, it examines the trend toward crafting more human-like task definitions and comprehensive evaluation frameworks to effectively gauge machine intelligence. This book serves as a roadmap for researchers aiming to grasp the bottlenecks in VOT capabilities and comprehend the gaps between current methodologies and human abilities, all geared toward advancing algorithmic intelligence. It also delves into the realm of data-centric AI, emphasizing the pivotal role of high-quality datasets and evaluation systems in the age of large language models (LLMs). Such systems are indispensable for training AI models while ensuring their safety and reliability. Utilizing VOT as a case study, the book offers detailed insights into these facets of data-centric AI research. Designed to cater to readers with foundational knowledge in computer vision, it employs diagrams and examples to facilitate comprehension, providing essential groundwork for understanding key technical components.
Computer Vision Eccv 2010
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Author : Kostas Daniilidis
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-08-30
Computer Vision Eccv 2010 written by Kostas Daniilidis and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-08-30 with Computers categories.
The six-volume set comprising LNCS volumes 6311 until 6313 constitutes the refereed proceedings of the 11th European Conference on Computer Vision, ECCV 2010, held in Heraklion, Crete, Greece, in September 2010. The 325 revised papers presented were carefully reviewed and selected from 1174 submissions. The papers are organized in topical sections on object and scene recognition; segmentation and grouping; face, gesture, biometrics; motion and tracking; statistical models and visual learning; matching, registration, alignment; computational imaging; multi-view geometry; image features; video and event characterization; shape representation and recognition; stereo; reflectance, illumination, color; medical image analysis.
Pattern Recognition And Computer Vision
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Author : Qingshan Liu
language : en
Publisher: Springer Nature
Release Date : 2023-12-27
Pattern Recognition And Computer Vision written by Qingshan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-27 with Computers categories.
The 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis.
Image Analysis And Recognition
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Author : Fakhri Karray
language : en
Publisher: Springer
Release Date : 2017-06-19
Image Analysis And Recognition written by Fakhri Karray and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-19 with Computers categories.
This book constitutes the thoroughly refereed proceedings of the 14th International Conference on Image Analysis and Recognition, ICIAR 2017, held in Montreal, QC, Canada, in July 2017. The 73 revised full papers presented were carefully reviewed and selected from 133 submissions. The papers are organized in the following topical sections: machine learning in image recognition; machine learning for medical image computing; image enhancement and reconstruction; image segmentation; motion and tracking; 3D computer vision; feature extraction; detection and classification; biomedical image analysis; image analysis in ophthalmology; remote sensing; applications.
Mems Technology For Biomedical Imaging Applications
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Author : Qifa Zhou
language : en
Publisher: MDPI
Release Date : 2019-10-23
Mems Technology For Biomedical Imaging Applications written by Qifa Zhou and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-23 with Technology & Engineering categories.
Biomedical imaging is the key technique and process to create informative images of the human body or other organic structures for clinical purposes or medical science. Micro-electro-mechanical systems (MEMS) technology has demonstrated enormous potential in biomedical imaging applications due to its outstanding advantages of, for instance, miniaturization, high speed, higher resolution, and convenience of batch fabrication. There are many advancements and breakthroughs developing in the academic community, and there are a few challenges raised accordingly upon the designs, structures, fabrication, integration, and applications of MEMS for all kinds of biomedical imaging. This Special Issue aims to collate and showcase research papers, short commutations, perspectives, and insightful review articles from esteemed colleagues that demonstrate: (1) original works on the topic of MEMS components or devices based on various kinds of mechanisms for biomedical imaging; and (2) new developments and potentials of applying MEMS technology of any kind in biomedical imaging. The objective of this special session is to provide insightful information regarding the technological advancements for the researchers in the community.
Computer Vision Accv 2012
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Author : Kyoung Mu Lee
language : en
Publisher: Springer
Release Date : 2013-03-27
Computer Vision Accv 2012 written by Kyoung Mu Lee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-27 with Computers categories.
The four-volume set LNCS 7724--7727 constitutes the thoroughly refereed post-conference proceedings of the 11th Asian Conference on Computer Vision, ACCV 2012, held in Daejeon, Korea, in November 2012. The total of 226 contributions presented in these volumes was carefully reviewed and selected from 869 submissions. The papers are organized in topical sections on object detection, learning and matching; object recognition; feature, representation, and recognition; segmentation, grouping, and classification; image representation; image and video retrieval and medical image analysis; face and gesture analysis and recognition; optical flow and tracking; motion, tracking, and computational photography; video analysis and action recognition; shape reconstruction and optimization; shape from X and photometry; applications of computer vision; low-level vision and applications of computer vision.
Computational Analysis Of Visual Motion
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Author : Amar Mitiche
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Computational Analysis Of Visual Motion written by Amar Mitiche and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Computers categories.
Image motion processing is important to machine vision systems because it can lead to the recovery of 3D structure and motion. Author Amar Mitiche offers a comprehensive mathematical treatment of this key subject in visual systems research. Mitiche examines the interpretation of point correspondences as well as the interpretation of straight line correspondences and optical flow. In addition, the author considers interpretation by knowledge-based systems and presents the relevant mathematical basis for 3D interpretation.
Image Based 3d Reconstruction Of Dynamic Objects Using Instance Aware Multibody Structure From Motion
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Author : Bullinger, Sebastian
language : en
Publisher: KIT Scientific Publishing
Release Date : 2020-08-26
Image Based 3d Reconstruction Of Dynamic Objects Using Instance Aware Multibody Structure From Motion written by Bullinger, Sebastian and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-26 with Computers categories.
"This work proposes a Multibody Structure from Motion (MSfM) algorithm for moving object reconstruction that incorporates instance-aware semantic segmentation and multiple view geometry methods. The MSfM pipeline tracks two-dimensional object shapes on pixel level to determine object specific feature correspondences, in order to reconstruct 3D object shapes as well as 3D object motion trajectories" -- Publicaciones de Arquitectura y Arte.
Advanced Intelligent Computing Technology And Applications
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Author : De-Shuang Huang
language : en
Publisher: Springer Nature
Release Date : 2025-08-25
Advanced Intelligent Computing Technology And Applications written by De-Shuang Huang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-25 with Computers categories.
This 20-volume set LNCS 15842-15861 constitutes - in conjunction with the 4-volume set LNAI 15862-15865 and the 4-volume set LNBI 15866-15869 - the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025. The total of 1206 regular papers were carefully reviewed and selected from 4032 submissions. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications".