商品描述
Discover the cutting-edge advancements in visual object tracking (VOT) with this comprehensive resource, designed to revolutionize how researchers and professionals approach tracking systems. This book presents deep learning techniques and multimodal fusion strategies, offering state-of-the-art solutions for robust and accurate object tracking in dynamic environments. With applications ranging from autonomous vehicles to intelligent surveillance, VOT has become a cornerstone of modern computer vision. By addressing challenges like scalability, real-time performance, and robustness, this book equips readers with the tools to navigate the rapidly evolving landscape of tracking systems. It's the first of its kind to seamlessly integrate single-modal and multimodal approaches, bridging the gap between foundational methods and emerging technologies. Explore key topics including Siamese networks, transformer-based models, RGB-LiDAR and RGB-thermal fusion, and spatio-temporal modeling. Gain insights into benchmark datasets, evaluation protocols, and future trends like large model transfer and cross-domain learning. Each chapter builds on the next, ensuring a structured progression from theoretical principles to practical applications. Whether you're a researcher, practitioner, or student in computer vision, artificial intelligence, or machine learning, this book is an indispensable guide to mastering VOT. A basic understanding of computer science and deep learning concepts is recommended to fully benefit from the material.
商品描述(中文翻譯)
探索視覺物體追蹤（VOT）的尖端進展，這本全面的資源旨在徹底改變研究人員和專業人士對追蹤系統的看法。本書介紹了深度學習技術和多模態融合策略，提供了在動態環境中進行穩健且準確的物體追蹤的最先進解決方案。
VOT 的應用範圍從自動駕駛車輛到智能監控，已成為現代計算機視覺的基石。通過解決可擴展性、實時性能和穩健性等挑戰，本書為讀者提供了應對快速發展的追蹤系統環境所需的工具。這是首本無縫整合單模態和多模態方法的書籍，彌合了基礎方法與新興技術之間的鴻溝。
探索關鍵主題，包括西亞米斯網絡（Siamese networks）、基於變壓器的模型（transformer-based models）、RGB-LiDAR 和 RGB-熱成像融合（RGB-thermal fusion）、以及時空建模（spatio-temporal modeling）。深入了解基準數據集、評估協議，以及大型模型轉移和跨域學習等未來趨勢。每一章都在前一章的基礎上構建，確保從理論原則到實際應用的結構性進展。
無論您是計算機視覺、人工智慧或機器學習的研究人員、從業者或學生，本書都是掌握 VOT 的不可或缺的指南。建議具備計算機科學和深度學習概念的基本理解，以充分受益於本書的內容。
作者簡介
Mengmeng Wang is an associate professor in the College of Computer Science and Technology, Zhejiang University of Technology. She earned her B.Sc., Master and the Ph.D. degrees in control science and engineering from Zhejiang University in 2015, 2018, and 2024. Her research focus on image/video understanding, text-to-video/image-to-video generation, computer vision, robotics, and intelligent transportation systems. Dr. Wang has published more than 50 papers at top journals and conferences, e.g., TPAMI, TIP, ICLR, NeurIPS, ICCV, AAAI, CVPR, ICRA, and IROS. She has served as area chairs of leading conferences in computer vision, such as ICCV. Xiangjie Kong is a professor at the College of Computer Science and Technology, Zhejiang University of Technology, China. He received his B.Sc. and Ph.D. degrees from Zhejiang University, in 2004 and 2009, respectively. Before joining Zhejiang University of Technology, he was an associate professor at the School of Software, Dalian University of Technology. Dr. Kong's research interests lies in social computing, mobile computing, and data science. He has authored over 200 scientific papers in international journals and conferences, with more than 180 indexed by ISI SCIE (with over 180 indexed by ISI SCIE). Dr. Kong is a Senior Member of the IEEE, a Distinguished Member of CCF, and is a member of ACM. Guojiang Shen is a professor at the College of Computer Science and Technology, Zhejiang University of Technology. He received his B.Sc. degree in Control Theory and Control Engineering and his Ph.D. degree in Control Science and Engineering from Zhejiang University in 1999 and 2004, respectively. His research expertise spans artificial intelligence, Big Data analytics, and intelligent transportation systems.
作者簡介(中文翻譯)
王萌萌是浙江工業大學計算機科學與技術學院的副教授。她於2015年、2018年和2024年分別獲得浙江大學控制科學與工程的學士、碩士和博士學位。她的研究重點包括圖像/視頻理解、文本到視頻/圖像到視頻生成、計算機視覺、機器人技術和智能交通系統。王博士在頂級期刊和會議上發表了超過50篇論文，例如TPAMI、TIP、ICLR、NeurIPS、ICCV、AAAI、CVPR、ICRA和IROS。她曾擔任計算機視覺領域主要會議的區域主席，如ICCV。
孔祥杰是浙江工業大學計算機科學與技術學院的教授。他於2004年和2009年分別獲得浙江大學的學士和博士學位。在加入浙江工業大學之前，他曾擔任大連理工大學軟件學院的副教授。孔博士的研究興趣包括社會計算、移動計算和數據科學。他在國際期刊和會議上發表了超過200篇科學論文，其中超過180篇被ISI SCIE索引。孔博士是IEEE的資深會員、CCF的傑出會員，並且是ACM的成員。
沈國江是浙江工業大學計算機科學與技術學院的教授。他於1999年和2004年分別獲得浙江大學控制理論與控制工程的學士學位和控制科學與工程的博士學位。他的研究專長涵蓋人工智慧、大數據分析和智能交通系統。
