Techniques For Detection And Tracking Of Multiple Objects
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Techniques For Detection And Tracking Of Multiple Objects
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Author : Mohamed Naiel
language : en
Publisher:
Release Date : 2017
Techniques For Detection And Tracking Of Multiple Objects written by Mohamed Naiel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
During the past decade, object detection and object tracking in videos have received a great deal of attention from the research community in view of their many applications, such as human activity recognition, human computer interaction, crowd scene analysis, video surveillance, sports video analysis, autonomous vehicle navigation, driver assistance systems, and traffic management. Object detection and object tracking face a number of challenges such as variation in scale, appearance, view of the objects, as well as occlusion, and changes in illumination and environmental conditions. Object tracking has some other challenges such as similar appearance among multiple targets and long-term occlusion, which may cause failure in tracking. Detection-based tracking techniques use an object detector for guiding the tracking process. However, existing object detectors usually suffer from detection errors, which may mislead the trackers, if used for tracking. Thus, improving the performance of the existing detection schemes will consequently enhance the performance of detection-based trackers. The objective of this research is two fold: (a) to investigate the use of 2D discrete Fourier and cosine transforms for vehicle detection, and (b) to develop a detection-based online multi-object tracking technique.The first part of the thesis deals with the use of 2D discrete Fourier and cosine transforms for vehicle detection. For this purpose, we introduce the transform-domain two-dimensional histogram of oriented gradients (TD2DHOG) features, as a truncated version of 2DHOG in the 2DDFT or 2DDCT domain. It is shown that these TD2DHOG features obtained from an image at the original resolution and a downsampled version from the same image are approximately the same within a multiplicative factor. This property is then utilized in developing a scheme for the detection of vehicles of various resolutions using a single classifier rather than multiple resolution-specific classifiers. Extensive experiments are conducted, which show that the use of the single classifier in the proposed detection scheme reduces drastically the training and storage cost over the use of a classifier pyramid, yet providing a detection accuracy similar to that obtained using TD2DHOG features with a classifier pyramid. Furthermore, the proposed method provides a detection accuracy that is similar or even better than that provided by the state-of-the-art techniques.In the second part of the thesis, a robust collaborative model, which enhances the interaction between a pre-trained object detector and a number of particle filter-based single-object online trackers, is proposed. The proposed scheme is based on associating a detection with a tracker for each frame. For each tracker, a motion model that incorporates the associated detections with the object dynamics, and a likelihood function that provides different weights for the propagated particles and the newly created ones from the associated detections are introduced, with a view to reduce the effect of detection errors on the tracking process. Finally, a new image sample selection scheme is introduced in order to update the appearance model of a given tracker. Experimental results show the effectiveness of the proposed scheme in enhancing the multi-object tracking performance.
Object Tracking Technology
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Author : Ashish Kumar
language : en
Publisher: Springer Nature
Release Date : 2023-10-27
Object Tracking Technology written by Ashish Kumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-27 with Computers categories.
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.
Autonomous And Intelligent Systems
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Author : Mohamed Kamel
language : en
Publisher: Springer
Release Date : 2011-06-28
Autonomous And Intelligent Systems written by Mohamed Kamel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-28 with Computers categories.
This book constitutes the refereed proceedings of the Second International Conference on Autonomous and Intelligent Systems, AIS 2011, held in Burnaby, BC, Canada, in June 2011, colocated with the International Conference on Image Analysis and Recognition, IACIAR 2011. The 40 revised full papers presented were carefully reviewed and selected from 62 submissions. The papers are organized in topical sections on autonomous and intelligent systems, intelligent and advanced control systems, intelligent sensing and data analysis, human-machine interaction, and intelligent circuit analysis and signal processing.
Moving Objects Detection Using Machine Learning
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Author : Navneet Ghedia
language : en
Publisher: Springer Nature
Release Date : 2022-01-01
Moving Objects Detection Using Machine Learning written by Navneet Ghedia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Technology & Engineering categories.
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.
Multiple Object Tracking Using Deep Learning Techniques
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Author : Laia Prat Ortonobas
language : en
Publisher:
Release Date : 2020
Multiple Object Tracking Using Deep Learning Techniques written by Laia Prat Ortonobas and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
This project has been devoted to (i) learning what Multiple Object Tracking (MOT) is, (ii) learning Python, one of the most used languages in Machine Learning and computer vision, and (iii) to evaluate a tracker (TrajTrack), currently being developed at the image processing group (GPI), against the UA-DETRAC dataset. The work has been divided in two parts. On the one hand, we have studied MOT and its main challenges, such as occlusions or identity switches, in order to follow multiple objects throughout a video sequence. To fully understand this problem, we have developed a multiple tennis ball tracker in Python from scratch. On the other hand, we have used TrajTrack, which is evaluated on a pedestrian dataset (MOT17), and adapted it to be evaluated against a car dataset (UA-DETRAC). For this, we have retrained the detection and re-identification models. We have obtained a 98.6% MOTA score for training and a 74.7% MOTA score for testing. These results are comparable with the state-of-the-art techniques.
Data Association For Multi Object Visual Tracking
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Author : Margrit Betke
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Data Association For Multi Object Visual Tracking written by Margrit Betke and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
In the human quest for scientific knowledge, empirical evidence is collected by visual perception. Tracking with computer vision takes on the important role to reveal complex patterns of motion that exist in the world we live in. Multi-object tracking algorithms provide new information on how groups and individual group members move through three-dimensional space. They enable us to study in depth the relationships between individuals in moving groups. These may be interactions of pedestrians on a crowded sidewalk, living cells under a microscope, or bats emerging in large numbers from a cave. Being able to track pedestrians is important for urban planning; analysis of cell interactions supports research on biomaterial design; and the study of bat and bird flight can guide the engineering of aircraft. We were inspired by this multitude of applications to consider the crucial component needed to advance a single-object tracking system to a multi-object tracking system—data association. Data association in the most general sense is the process of matching information about newly observed objects with information that was previously observed about them. This information may be about their identities, positions, or trajectories. Algorithms for data association search for matches that optimize certain match criteria and are subject to physical conditions. They can therefore be formulated as solving a "constrained optimization problem"—the problem of optimizing an objective function of some variables in the presence of constraints on these variables. As such, data association methods have a strong mathematical grounding and are valuable general tools for computer vision researchers. This book serves as a tutorial on data association methods, intended for both students and experts in computer vision. We describe the basic research problems, review the current state of the art, and present some recently developed approaches. The book covers multi-object tracking in two and three dimensions. We consider two imaging scenarios involving either single cameras or multiple cameras with overlapping fields of view, and requiring across-time and across-view data association methods. In addition to methods that match new measurements to already established tracks, we describe methods that match trajectory segments, also called tracklets. The book presents a principled application of data association to solve two interesting tasks: first, analyzing the movements of groups of free-flying animals and second, reconstructing the movements of groups of pedestrians. We conclude by discussing exciting directions for future research.
Fundamentals Of Object Tracking
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Author :
language : en
Publisher: Cambridge University Press
Release Date : 2011-07-28
Fundamentals Of Object Tracking written by and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-28 with Mathematics categories.
Introduces object tracking algorithms from a unified, recursive Bayesian perspective, along with performance bounds and illustrative examples.
Tracking Of Moving Objects In Video Sequences
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Author : S R Boselin Prabhu
language : en
Publisher: Educreation Publishing
Release Date : 2018-09-10
Tracking Of Moving Objects In Video Sequences written by S R Boselin Prabhu and has been published by Educreation Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-10 with Education categories.
Object tracking could be a terribly difficult task within the presence of variability illumination condition, background motion, complicated object form, partial and full object occlusions. The main intention of an object trailer is to make the path of an object over time by characteristic its position in all frames of the video. This book is intended to educate the researchers in the field of tracking of moving object(s) in a video sequence. This book provides a path for the researchers to identify the works done by others in the same field and thereby to figure out the gap in the current knowledge. This book is organized into three Modules. Module 1 talks about the introduction of object detection and tracking. Module 2 discusses about the various studies of object tracking and motion detection. The views of the various authors about this hot research topic are discussed in this Module and Module 3 gives the conclusion of the entire research review.Object tracking could be a terribly difficult task within the presence of variability illumination condition, background motion, complicated object form, partial and full object occlusions. The main intention of an object trailer is to make the path of an object over time by characteristic its position in all frames of the video. This book is intended to educate the researchers in the field of tracking of moving object(s) in a video sequence. This book provides a path for the researchers to identify the works done by others in the same field and thereby to figure out the gap in the current knowledge. This book is organized into three Modules. Module 1 talks about the introduction of object detection and tracking. Module 2 discusses about the various studies of object tracking and motion detection. The views of the various authors about this hot research topic are discussed in this Module and Module 3 gives the conclusion of the entire research review.
Moving Object Detection Using Background Subtraction
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Author : Soharab Hossain Shaikh
language : en
Publisher: Springer
Release Date : 2014-06-20
Moving Object Detection Using Background Subtraction written by Soharab Hossain Shaikh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-20 with Computers categories.
This Springer Brief presents a comprehensive survey of the existing methodologies of background subtraction methods. It presents a framework for quantitative performance evaluation of different approaches and summarizes the public databases available for research purposes. This well-known methodology has applications in moving object detection from video captured with a stationery camera, separating foreground and background objects and object classification and recognition. The authors identify common challenges faced by researchers including gradual or sudden illumination change, dynamic backgrounds and shadow and ghost regions. This brief concludes with predictions on the future scope of the methods. Clear and concise, this brief equips readers to determine the most effective background subtraction method for a particular project. It is a useful resource for professionals and researchers working in this field.
Proceedings 2001 Ieee Workshop On Multi Object Tracking July 8 2001 Vancouver British Columbia Canada
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Author : IEEE Computer Society
language : en
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Release Date : 2001
Proceedings 2001 Ieee Workshop On Multi Object Tracking July 8 2001 Vancouver British Columbia Canada written by IEEE Computer Society and has been published by Institute of Electrical & Electronics Engineers(IEEE) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
Annotation Contains 12 papers from a July 2001 workshop on visual tracking of multiple objects in computer vision. Topics discussed include unified multi-camera detection and tracking using region-matching, maintaining the identity of multiple vehicles as they travel through a video network, tracking body parts of multiple people, joint likelihood methods for mitigating visual tracking disturbances, and combined segmentation and tracking of overlapping objects with feedback. Other subjects include tracking and recognizing two-person interactions in outdoor image sequences, multiple camera fusion for multi-object tracking, tracking multiple people with a multi-camera system, and engineering statistics for multi-object tracking. This volume lacks a subject index. c. Book News Inc.