US-China Workshop on Computer Vision

朱松春(加州大学洛杉矶分校)美国-中国计算机视觉研讨会加州大学洛杉矶分校的朱松春博士的提案涉及美国-中国在计算视觉(包括图像分析、模式识别、图像处理、医学图像等)领域的研讨会。2005年9月1日至3日，中国在鄂州莲花山学院。该研讨会是一项雄心勃勃的计划的一部分，该计划旨在建立美国和中国两国视觉科学家之间的长期互利合作，并在解决计算视觉领域的一些根本瓶颈方面结合互补的努力和能力。一个广为人知的瓶颈是收集由人类用户以一种通用格式解析的通用数据集(大约100,000幅图像)。收集和分析如此庞大的数据集需要所有视觉领域的专家的共同努力。与会者将相互学习经验，并在研讨会上讨论共同的模式。建立数据集将使美国和中国未来的视觉研究人员受益，并加强参与机构之间的合作。美国团队包括研究人员、初级科学家和来自全国各地大学的学生参加美国-中国联合研讨会。中国对口小组由中国国家科学基金、微软亚洲研究院等资助，成员包括中国科学院自动化所、华中科技大学模式识别与人工智能研究所、微软亚洲研究院等学者。

ABSTRACTOISE-0527138Zhu, Song-Chun (University of California at Los Angeles) U.S.-China Workshop on Computer Vision This proposal from Dr. Song-Chun Zhu of UCLA involves a U.S.-China Workshop in the area of computational vision (including image analysis, pattern recognition, image processing, medical images, etc.) at the Lotus Hill Institute in Ezhou, China on September 1-3, 2005. The workshop is part of an ambitious plan to establish a long-term mutually beneficial collaboration between vision scientists in both the U.S. and China, and to combine complementary efforts and capabilities in addressing some fundamental bottlenecks in computational vision. A widely acknowledged bottleneck is collecting a common data set (on the order of 100,000 images) parsed by human users in a common format. Collecting and parsing such a large data set requires the collective efforts from experts in all vision areas. Participants will learn from each other's experience and discuss a common format in the workshop. Establishing the data set will benefit vision researchers in both U.S. and China in the future and enhance collaboration among participating institutions.The U.S. team includes researchers, junior scientists, and students to attend a joint U.S.-China workshop from universities across the country. The Chinese counterpart group, funded by the National Science Foundation of China, Microsoft Research Institute of Asia, and others, includes scholars from the Institute of Automation of the Chinese Academy of Science; Institute of Pattern Recognition and Artificial Intelligence, HuaZhong University of Science and Technology; and Microsoft Research Institute Asia.