商品描述
As 3D vision reshapes industries from augmented reality to autonomous systems, a critical challenge emerges: How can we efficiently process massive point cloud data without sacrificing quality? This book delivers the answer by unveiling the first unified framework that integrates AI-based coding algorithms, international standards (MPEG/JPEG/AVS), and real-world implementations--a breakthrough absent in existing literature. This book is a must-read for researchers, practitioners, and students who are interested in the interdisciplinary fields of artificial intelligence, data compression, immersive media, and 3D vision applications. Featuring detailed discussions on both static and dynamic point cloud coding, the book systematically unpacks innovative methods, international standards, and open-source solutions. It addresses quality assessment, perception modeling, and artifact removal techniques--areas that pose significant challenges yet hold transformative potential for 3D data processing. By presenting comparative analyses of prominent standards, such as the deep learning-based point cloud coding standards from MPEG, JPEG, and AVS, alongside emerging AI-enhanced coding frameworks, the book equips professionals with the insights necessary to navigate and shape the future of multimedia communication and 3D vision technologies. With its clear, segmented structure and targeted content, this book not only addresses current academic debates but also paves the way for future research and industrial applications. Readers are guided through a rich array of topics--from deep neural network fundamentals to lightweight implementations and rendering systems--ensuring they gain a robust, practical understanding of AI-based point cloud coding. Whether you are looking to advance your research, enhance your technical skills, or simply explore the forefront of 3D vision innovation, this book offers the critical tools and perspectives needed to excel.
商品描述(中文翻譯)
隨著3D視覺重塑從擴增實境到自主系統的各個行業，一個關鍵挑戰浮現：我們如何能在不犧牲品質的情況下有效處理大量的點雲數據？本書提供了解答，揭示了第一個統一框架，整合了基於AI的編碼算法、國際標準（MPEG/JPEG/AVS）以及實際應用——這在現有文獻中是前所未有的突破。本書是對於對人工智慧、數據壓縮、沉浸式媒體和3D視覺應用等跨學科領域感興趣的研究者、實務工作者和學生的必讀之作。
本書詳細討論了靜態和動態點雲編碼，系統性地解析了創新方法、國際標準和開源解決方案。它探討了品質評估、感知建模和工件去除技術——這些領域面臨著重大挑戰，但同時也對3D數據處理具有變革潛力。通過對MPEG、JPEG和AVS等知名標準的深度學習基於點雲編碼標準以及新興的AI增強編碼框架進行比較分析，本書為專業人士提供了必要的見解，以導航和塑造多媒體通信和3D視覺技術的未來。
本書以清晰、分段的結構和針對性的內容，不僅針對當前的學術辯論，還為未來的研究和工業應用鋪平了道路。讀者將被引導通過一系列豐富的主題——從深度神經網絡基礎到輕量級實現和渲染系統——確保他們獲得對基於AI的點雲編碼的堅實、實用理解。無論您是希望推進研究、提升技術技能，還是僅僅想探索3D視覺創新的前沿，本書都提供了成功所需的關鍵工具和觀點。
作者簡介
Wei Gao is an associate professor with tenure at the School of Electronic and Computer Engineering, Peking University, Shenzhen, China. He earned his Ph.D. in Computer Science from City University of Hong Kong in February 2017. Dr. Gao's research focuses on multimedia coding and processing, 3D vision and multimodal learning--areas directly relevant to the topics explored in this book. With over 200 high-quality technical papers published, he has made significant contributions to multimedia coding standardization by more than 30 adopted technical proposals. He is also the author or coauthor of three influential books, namely AI-based Image and Video Coding: Methods, Standards, and Applications; Point Cloud Compression: Technologies and Standardization and Deep Learning for 3D Point Clouds, published with Springer Nature. Beyond his robust academic credentials, Dr. Gao actively serves on the editorial board of IEEE Transactions on Image Processing (TIP), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), IEEE Transactions on Multimedia (TMM), and holds elected memberships in both the IEEE Multimedia Systems and Applications Technical Committee (MSA-TC) and IEEE Visual Signal Processing and Communications Technical Committee (VSPC-TC). He leads several open-source projects, including OpenAICoding, OpenPointCloud, OpenDatasets, and OpenAIDring, which have become valuable resources for the research community. As a senior member of IEEE, he is also a frequent speaker at international conferences, where he shares his expertise on multimedia computing and artificial intelligence technologies.
作者簡介(中文翻譯)
高偉是中國北京大學深圳校區電子與計算機工程學院的終身副教授。他於2017年2月在香港城市大學獲得計算機科學博士學位。高博士的研究專注於多媒體編碼與處理、3D視覺和多模態學習，這些領域與本書探討的主題直接相關。高博士已發表超過200篇高品質的技術論文，並通過超過30項被採納的技術提案對多媒體編碼標準化做出了重要貢獻。他還是三本有影響力的書籍的作者或合著者，分別是《基於AI的影像與視頻編碼：方法、標準與應用》、《點雲壓縮：技術與標準化》以及《3D點雲的深度學習》，這些書籍均由Springer Nature出版。
除了堅實的學術背景外，高博士還積極擔任《IEEE影像處理期刊》（TIP）、《IEEE視頻技術電路與系統期刊》（TCSVT）、《IEEE多媒體期刊》（TMM）的編輯委員會成員，並在IEEE多媒體系統與應用技術委員會（MSA-TC）和IEEE視覺信號處理與通信技術委員會（VSPC-TC）中擔任選舉成員。他領導幾個開源項目，包括OpenAICoding、OpenPointCloud、OpenDatasets和OpenAIDring，這些項目已成為研究社群的重要資源。作為IEEE的資深會員，他也是國際會議的常客演講者，分享他在多媒體計算和人工智慧技術方面的專業知識。
