Human Centric Visual Analysis with Deep Learning
暫譯: 以深度學習為基礎的人本視覺分析
Lin, Liang, Zhang, Dongyu, Luo, Ping
- 出版商: Springer
- 出版日期: 2019-11-27
- 售價: $6,400
- 貴賓價: 9.5 折 $6,080
- 語言: 英文
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 9811323860
- ISBN-13: 9789811323867
-
相關分類:
DeepLearning
海外代購書籍(需單獨結帳)
商品描述
This book introduces the applications of deep learning in various human centric visual analysis tasks, including classical ones like face detection and alignment and some newly rising tasks like fashion clothing parsing. Starting from an overview of current research in human centric visual analysis, the book then presents a tutorial of basic concepts and techniques of deep learning. In addition, the book systematically investigates the main human centric analysis tasks of different levels, ranging from detection and segmentation to parsing and higher-level understanding. At last, it presents the state-of-the-art solutions based on deep learning for every task, as well as providing sufficient references and extensive discussions.
Specifically, this book addresses four important research topics, including 1) localizing persons in images, such as face and pedestrian detection; 2) parsing persons in details, such as human pose and clothing parsing, 3) identifying and verifying persons, such as face and human identification, and 4) high-level human centric tasks, such as person attributes and human activity understanding.
This book can serve as reading material and reference text for academic professors / students or industrial engineers working in the field of vision surveillance, biometrics, and human-computer interaction, where human centric visual analysis are indispensable in analysing human identity, pose, attributes, and behaviours for further understanding.
商品描述(中文翻譯)
這本書介紹了深度學習在各種以人為中心的視覺分析任務中的應用，包括經典的任務如臉部檢測和對齊，以及一些新興的任務如時尚服裝解析。書中首先概述了當前以人為中心的視覺分析研究，然後介紹了深度學習的基本概念和技術的教程。此外，書中系統性地探討了不同層次的主要以人為中心的分析任務，從檢測和分割到解析和更高層次的理解。最後，書中針對每個任務呈現了基於深度學習的最先進解決方案，並提供了充分的參考資料和廣泛的討論。
具體而言，本書針對四個重要的研究主題，包括 1) 在影像中定位人物，例如臉部和行人檢測；2) 詳細解析人物，例如人體姿勢和服裝解析；3) 識別和驗證人物，例如臉部和人體識別；以及 4) 高層次的以人為中心的任務，例如人物屬性和人類活動理解。
這本書可以作為學術教授/學生或在視覺監控、生物識別和人機互動領域工作的工業工程師的閱讀材料和參考文本，其中以人為中心的視覺分析對於分析人類身份、姿勢、屬性和行為以進一步理解是不可或缺的。
作者簡介
Liang Lin is a Professor at the School of Data and Computer Science, Sun Yat-sen University (SYSU), China. He received his Bachelor and Ph.D. degree in Computer Science from the Beijing Institute of Technology (BIT), China, in 1999 and 2008, respectively. From 2006 to 2007, he was a joint Ph.D. student at the Department of Statistics, University of California, Los Angeles (UCLA). His research focuses on new models, algorithms and systems for intelligent processing and understanding of visual data. He has been supported by several programs or funds, such as the Ministry of Education (China) "Program for New Century Excellent Talents" in 2012, and the Guangdong NSFs for Distinguished Young Scholars in 2013. He received the Best Paper Runners-Up Award in ACM NPAR 2010, Google Faculty Award in 2012, and Best Student Paper Award in IEEE ICME 2014.
Dongyu Zhang is a Research Scientist at the School of Data and Computer Science, Sun Yat-sen University (SYSU), China. He received his Master's and Ph.D. degree in Computer Science from the Harbin Institute of Technology (HIT), China, in 2003 and 2008, respectively. His current research interests include deep learning, image modeling and biometrics.
Ping Luo is a Research Assistant Professor at the Chinese University of Hong Kong, where he received his Ph.D. degree in 2014. His research interests focus on machine learning and computer vision, including deep learning optimization and theory, face and pedestrian analysis, image parsing, and large-scale object recognition and detection. Dr. Luo has published more than 60 papers in the top-tier academic journals and conferences, including TPAMI, IJCV, NIPS, ICML, and CVPR. His papers have over 6000 citations in Google Scholar. Because of his contribution in deep learning and computer vision, Dr. Luo was awarded the Microsoft Research Fellowship in 2013. Only ten scholars in the Asia-Pacific area received this award each year. Besides, he was elected the Hong Kong PhD Fellowship in 2011 by the Research Grants Council of Hong Kong.
Wangmeng Zuo is a Professor at the School of Computer Science and Technology, Harbin Institute of Technology (HIT), China. He received his Ph.D. degree in Computer Application Technology from the HIT in 2007. From July 2004 to December 2004, from November 2005 to August 2006, and from July 2007 to February 2008, he was a Research Assistant at the Department of Computing, Hong Kong Polytechnic University. From August 2009 to February 2010, he was a Visiting Professor at Microsoft Research Asia. His current research interests include image restoration, image editing, image classification, object detection, and visual tracking. Dr. Zuo is an Associate Editor of the IET Biometrics, and a Guest Editor of Neurocomputing, Pattern Recognition, and IEEE Transactions on Neural Network and Learning Systems.
作者簡介(中文翻譯)
梁林是中國中山大學（SYSU）數據與計算機科學學院的教授。他於1999年和2008年分別在北京理工大學（BIT）獲得計算機科學的學士和博士學位。從2006年到2007年，他是加州大學洛杉磯分校（UCLA）統計系的聯合博士生。他的研究專注於視覺數據的智能處理和理解的新模型、算法和系統。他曾獲得多個計劃或基金的支持，例如2012年中國教育部的「新世紀優秀人才計劃」，以及2013年廣東省優秀青年學者的NSF資助。他在2010年ACM NPAR獲得最佳論文亞軍獎，2012年獲得Google Faculty Award，並在2014年IEEE ICME獲得最佳學生論文獎。
張冬宇是中國中山大學（SYSU）數據與計算機科學學院的研究科學家。他於2003年和2008年分別在哈爾濱工業大學（HIT）獲得計算機科學的碩士和博士學位。他目前的研究興趣包括深度學習、圖像建模和生物識別技術。
羅平是香港中文大學的研究助理教授，於2014年獲得博士學位。他的研究興趣集中在機器學習和計算機視覺，包括深度學習優化和理論、人臉和行人分析、圖像解析以及大規模物體識別和檢測。羅博士在頂級學術期刊和會議上發表了60多篇論文，包括TPAMI、IJCV、NIPS、ICML和CVPR。他的論文在Google Scholar上被引用超過6000次。因為他在深度學習和計算機視覺方面的貢獻，羅博士於2013年獲得微軟研究獎學金。每年亞太地區僅有十位學者獲得此獎。此外，他於2011年被香港研究資助局選為香港博士研究生獎學金得主。
左望萌是中國哈爾濱工業大學（HIT）計算機科學與技術學院的教授。他於2007年在HIT獲得計算機應用技術的博士學位。從2004年7月到2004年12月，從2005年11月到2006年8月，以及從2007年7月到2008年2月，他曾在香港理工大學計算系擔任研究助理。從2009年8月到2010年2月，他是微軟亞洲研究院的訪問教授。他目前的研究興趣包括圖像修復、圖像編輯、圖像分類、物體檢測和視覺追蹤。左博士是IET Biometrics的副編輯，並擔任Neurocomputing、Pattern Recognition和IEEE Transactions on Neural Network and Learning Systems的客座編輯。
