Computer Vision: Statistical Models for Marr's Paradigm
暫譯: 計算機視覺：Marr範式的統計模型

Zhu, Song-Chun, Wu, Ying Nian

Computer Vision: Statistical Models for Marr's Paradigm
  • 出版商: Springer
  • 出版日期: 2024-03-16
  • 售價: $2,100
  • 貴賓價: 9.5 折 $1,995
  • 語言: 英文
  • 頁數: 357
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3030965325
  • ISBN-13: 9783030965327
  • 相關分類: Computer Vision

    • 海外代購書籍(需單獨結帳)

商品描述

As the first book of a three-part series, this book is offered as a tribute to pioneers in vision, such as Béla Julesz, David Marr, King-Sun Fu, Ulf Grenander, and David Mumford. The authors hope to provide foundation and, perhaps more importantly, further inspiration for continued research in vision. This book covers David Marr's paradigm and various underlying statistical models for vision. The mathematical framework herein integrates three regimes of models (low-, mid-, and high-entropy regimes) and provides foundation for research in visual coding, recognition, and cognition. Concepts are first explained for understanding and then supported by findings in psychology and neuroscience, after which they are established by statistical models and associated learning and inference algorithms. A reader will gain a unified, cross-disciplinary view of research in vision and will accrue knowledge spanning from psychology to neuroscience to statistics.

商品描述(中文翻譯)

作為三部曲系列的第一本書，本書是對視覺領域先驅者的致敬，如 Béla Julesz、David Marr、King-Sun Fu、Ulf Grenander 和 David Mumford。作者希望能提供基礎，或許更重要的是，為持續的視覺研究提供進一步的靈感。本書涵蓋了 David Marr 的範式以及各種視覺的基本統計模型。這裡的數學框架整合了三種模型範疇（低熵、中熵和高熵範疇），並為視覺編碼、識別和認知的研究提供基礎。概念首先以易於理解的方式解釋，然後通過心理學和神經科學的研究結果進行支持，之後再由統計模型及相關的學習和推理算法來建立。讀者將獲得一個統一的跨學科視覺研究觀點，並累積從心理學到神經科學再到統計學的知識。

作者簡介

Song-Chun Zhu is Chair Professor at Peking and Tsinghua Universities, Director of Beijing Institute for General Artificial Intelligence, and Founding Dean of School of Artificial Intelligence at Peking University. He received his M.S. degree and Ph.D. degree in computer science from Harvard University in 1994 and 1996 respectively, under the supervision of David Mumford. He joined UCLA in 2002 as an Associate Professor. He became a full professor at UCLA in 2006 and returned to China in 2020. While at UCLA, Zhu was the director of Vision, Cognition, Learning, and Autonomy (VCLA) Lab. His research areas include computer vision, statistical modeling, cognitive reasoning, robot autonomy and AI. He has received many awards for his research contributions, including Marr Prize in 2003, and Helmholtz Test-of-Time Award in 2013. He is a fellow of IEEE Computer Society.

Ying Nian Wu is a professor in Department of Statistics, UCLA. He received his A.M. degree and Ph.D. degree in statistics from Harvard University in 1994 and 1996 respectively, under the supervision of Donald Rubin. He was an assistant professor in Department of Statistics, University of Michigan from 1997 to 1999. He joined UCLA in 1999. He was an assistant professor from 1999 to 2001. He was an associate professor from 2001 to 2006. He has been a full professor since 2006. Wu's research areas include representation learning, generative modeling, computer vision, computational neuroscience, and bioinformatics.





作者簡介(中文翻譯)

朱松春是北京大學和清華大學的講座教授，北京通用人工智慧研究所所長，以及北京大學人工智慧學院的創院院長。他於1994年和1996年分別在哈佛大學獲得計算機科學碩士和博士學位，指導教授為David Mumford。他於2002年加入加州大學洛杉磯分校（UCLA）擔任副教授，並於2006年晉升為正教授，於2020年回到中國。在UCLA期間，朱教授是視覺、認知、學習與自主（VCLA）實驗室的主任。他的研究領域包括計算機視覺、統計建模、認知推理、機器人自主和人工智慧。他因其研究貢獻獲得多項獎項，包括2003年的Marr獎和2013年的Helmholtz Test-of-Time獎。他是IEEE計算機學會的會士。

吳英年是加州大學洛杉磯分校（UCLA）統計系的教授。他於1994年和1996年分別在哈佛大學獲得統計學碩士和博士學位，指導教授為Donald Rubin。他於1997年至1999年在密西根大學統計系擔任助理教授，並於1999年加入UCLA。1999年至2001年期間擔任助理教授，2001年至2006年期間擔任副教授，自2006年以來一直擔任正教授。吳教授的研究領域包括表示學習、生成建模、計算機視覺、計算神經科學和生物資訊學。

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