object_tracking2022: Object Tracking in Video Streams |
Website | https://sites.google.com/view/objecttracking2022/home |
Submission link | https://easychair.org/conferences/?conf=object-tracking2022 |
Visual tracking is one of the most eminent fields of computer vision. Visual tracking is about localizing the target in the first frame and keep the track in the subsequent frames of a video frame. Generally, tracking a target involves three steps namely, feature extraction, target localization and target optimization. First step involves the extraction of feature in order to describe the target in the scene. Handcrafted features such as color, texture, histogram of gradient can be extracted from target. Apart from vision information, thermal profile, infrared, and audio can also be extracted for target representation. In addition, deep features can be extracted either from single layer or multiple layer of a deep learning based architecture. Next step in visual tracking is target localization. Localization of the target in a video stream is tedious due to the dynamic environmental variations that originate in real-time. Numerous algorithms have been proposed under traditional approach due to the computational benefits and simplicity in implementation. Now a day, there is a paradigm shift in tracking algorithm to deep learning based algorithms. Deep learning based algorithm provides more precise estimation of target in terms of accuracy even in tough tracking scenarios. In the end, the target optimization step involves for optimal localization of the target in presence of challenges to prevent the tracker’s drift.
In the recent year, with the advancement in technology visual tracking extends to track multi-target present in the scene rather estimating location for single target only. In contract 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 in order 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 represents 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.
Submission Guidelines
All the contributors are invited to submit their proposal in Proper PDF file specifying:
a. Title
b. List of Authors--Mention Clearly "The Corresponding Author"
c. Abstract- 250 to 300 words
d. 6 Keywords
e. Table of Contents
The Submission for the Proposal is welcome till October 30, 2021 via Easychair Link: https://easychair.org/conferences/?conf=object-tracking2022
List of Topics
Chapter-1: Introduction to visual tracking in video stream
Chapter-2: Target saliency prediction and feature extraction for visual tracking
Chapter-3: Single target visual tracking in video stream
Chapter-4: Deep learning based single target tracking in video stream
Chapter-5: From single target visual tracking to multi-target visual tracking
Chapter-6: Deep learning based multi-target tracking
Chapter-7: Analysis of traditional visual tracking methods and deep learning based methods
Chapter-8: Computational comparison of single target visual tracker to multi-target visual tracker
Chapter-9: Application of visual tracking from single target to multi target
Chapter-10: Future Trends of visual tracking
(Kindly Note: Any Other Chapter, apart from above chapters is all welcome, but should be within the scope of the book)
Editors
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Dr. Ashish Kumar, Bharati Vidyapeeth's College of Engineering, India
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Dr. Rachna Jain, Bharati Vidyapeeth's College of Engineering, India
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Dr. V. Ajantha Devi, AP3 Solutions, India
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Dr. Anand Nayyar, Duy Tan University, Da Nang, Viet Nam
Contact
All questions about submissions or any queries, contact the following:
Dr. Anand Nayyar...Email: anandnayyar@duytan.edu.vn; Mobile (WhatsApp): +91-9878327635
Dr. V. Ajantha Devi....Email: ap3solutionsresearch@gmail.com ; Mobile: +91 94442 84265