Frontiers of Vision: A collaborative workshop on Computer Vision and its role in application with broad societal impact

摘要IIS-0513521 Soatto，Stefano加州大学洛杉矶分校视觉前沿：计算机视觉及其在具有广泛社会影响的应用中的作用的协作研讨会计算机视觉是一个相对年轻但发展迅速的领域。学术界正在迅速发展，例如，计算机视觉和模式识别会议的提交数量，自1998年以来增加了两倍多（1998年为453，2000年为466，2001年为920，2003年为1100，2004年为1300，2005年为1500）。这种增长部分是由于在安全和监控应用、医学成像、机器人技术、持久ISR等方面对视觉使用的需求增加。九十年代中期，随着商用现成硬件的可用性，实现了一个关键的垫脚石，可以真实的实时采集和处理成像数据，从而实现了一系列全新的应用，其中视觉被用作实时控制应用环路中的传感器。视觉在从交通到太空、娱乐、环境监测、医学和安全等具有广泛社会和科学影响的问题中发挥着关键作用。从微软到西门子、通用电气、三菱、本田等大型工业集团在视觉研究方面的投资增加也证明了视觉在应用中发挥的越来越大的作用。尽管有这样一个蓬勃发展的趋势，学术和研究界仍然严重分散。研究人员来自不同的背景（数学，物理学，工程学，计算机科学，神经科学），并使用不同的技术语言（从图论到偏微分方程，信息论到动力系统和控制理论）。该社区还被严重分割为子领域，很少有成功的尝试纵向整合不同的方法。与其他拥有一套通用的分析工具、统一的语言或一套通用的基准任务的学科不同，计算机视觉仍然是针对不同问题的不同方法的集合，没有统一的理论，甚至没有不同方法或通用实验基准之间的理性比较。本次研讨会的目标是为领先的研究人员提供一个场所，分享他们对计算机视觉未来发展方向的看法，从不同领域建立联系，并提出帮助提高社区在具有广泛社会影响的应用中的影响的方法。

AbstractIIS-0513521Soatto, StefanoUniversity of California-Los AngelesFrontiers of Vision: A collaborative workshop on Computer Vision and its role in application with broad societal impactComputer Vision is a relatively young but rapidly evolving field. The academic community is growing rapidly, as measured for instance by the number of submissions to the Computer Vision and Pattern Recognition conferences, which more than tripled since 1998 (submission was 453 in 1998, 466 in 2000, 920 in 2001, 1100 in 2003, 1300 in 2004, and 1500 in 2005). Such a growth is partly fueled by an increased demand for the use of vision in security and monitoring applications, medical imaging, robotics, persistent ISR, etc. A key stepping-stone was also achieved in the mid nineties with the availability of commercial off-the-shelf hardware to acquire and process imaging data in real time, thus enabling an entire new host of applications where vision is to be used as a sensor in the loop of real-time control applications. Vision is coming to play a key role in problems of broad societal and scientific impact from transportation to space, to entertainment, to environmental monitoring, to medicine, and to security. The increasing role that vision plays in applications is also documented by the increased investment by large industrial groups in vision research, from Microsoft to Siemens, General Electric, Mitsubishi, Honda etc.Despite such a booming trend, the academic and research community remains heavily fragmented. Researchers come to vision from different backgrounds (mathematics, physics, engineering, computer science, neuroscience) and speak different technical languages (from graph theory to partial differential equations to information theory to dynamical systems and control theory). The community is also heavily segmented into sub-areas with few successful attempts to vertically integrate different approaches. Unlike other disciplines that have a common set of analytical tools and speak a unified language or that have a common set of benchmark tasks, Computer Vision remains a collection of separate approaches to separate problems, with no unifying theory, or even rational comparison between different approaches or common experimental benchmarks. The goal of this workshop is to provide a venue for leading researchers to share their views on the future directions in Computer Vision, draw connections from different areas, and propose ways to help improve the impact of the community in applications that have broad societal consequences.