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Visual object trackingan evaluation perspective /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Visual object trackingby Xin Zhao, Shiyu Hu, Xu-Cheng Yin.
其他題名:	an evaluation perspective /
作者:	Zhao, Xin.
其他作者:	Hu, Shiyu.
出版者:	Singapore :Springer Nature Singapore :2025.
面頁冊數:	xv, 199 p. :ill. (chiefly color), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Computer vision.
電子資源:	https://doi.org/10.1007/978-981-96-4558-9
ISBN:	9789819645589$q(electronic bk.)

Visual object trackingan evaluation perspective /
Zhao, Xin.

Visual object trackingan evaluation perspective /[electronic resource] :by Xin Zhao, Shiyu Hu, Xu-Cheng Yin. - Singapore :Springer Nature Singapore :2025. - xv, 199 p. :ill. (chiefly color), digital ;24 cm. - Advances in computer vision and pattern recognition,2191-6594. - Advances in computer vision and pattern recognition..

Task Introduction -- Experimental Environment -- Algorithms -- Humans -- Machine-to-Machine Comparisons -- Visual Turing Test: Machine-to-Machine Comparisons -- More Human-like Task Design -- More Realistic Data Environment -- More Human-like Executors -- More Intelligent Evaluation.

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.

ISBN: 9789819645589$q(electronic bk.)

Standard No.: 10.1007/978-981-96-4558-9doiSubjects--Topical Terms:

200113
Computer vision.

LC Class. No.: TA1634

Dewey Class. No.: 006.37

Visual object trackingan evaluation perspective /
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