RI: Integrating Illumination, Motion and Shape Models for Video Analysis

提案0712253 PI：Amit Roy ChowdhuryInstitution：加州大学河滨分校合伙PI：Gopi Meenakshisundaram Institution：加州大学欧文分校标题：集成用于视频分析的照明、运动和形状模型本项目涉及视频分析的基础研究计划，该计划建立在一个新的框架之上，用于集成不同的独立成像模式-照明条件、对象形状、运动和表面反射。重点研究了基于光照、运动和形状学习模型的视频中姿态和光照不变目标识别问题。我们还利用从自然视频中学习的光照模型开发了新颖的场景重光方法。这项拟议的研究首先开发了一个数学框架，将视频序列的外观与照明条件、被成像对象的运动以及它们的形状和表面属性联系起来。此后，它解决了从视频识别的逆问题。总体的数学方法是将精确的几何模型和统计数据分析工具相结合，从而将精度和稳健性结合在一起，这一研究将有利于大量现有的应用，并创造出依赖于在变化的环境条件下有效跟踪目标的新的应用。它们包括在国土安全、核设施监测和边境安全等国家优先领域的应用，在视频通信、多媒体数据库和娱乐等商业利益领域的应用，在野生动物和环境监测等社会事业中的应用，以及依赖视频分析的医疗和生物应用。通过从自然视频中学习物体的运动和光照来实现场景重光照也将对创建逼真的虚拟环境产生重大影响。该项目的进展将定期在http://www.ee.ucr.edu/~amitrc/JMIS.htm上更新

Proposal 0712253 PI: Amit Roy ChowdhuryInstitution: University of California - RiversideCo-PI: Gopi MeenakshisundaramInstitution: University of California - IrvineTitle: Integrating Illumination, Motion and Shape Models for Video AnalysisThis project involves a fundamental research program in video analysis that is built upon a novel framework for integrating different independent modalities of image formation - illumination conditions, object shape, motion and surface reflectance. We focus on the problem of pose and illumination invariant object recognition in video, based on learned models of lighting, motion and shape. We also develop novel scene relighting methods using the illumination models learned from natural videos. The proposed research proceeds by first developing a mathematical framework that relates the appearance of a video sequence with the lighting conditions, motion of the objects being imaged, and their shape and surface properties. Thereafter, it addresses the inverse problem of recognition from video. The overall mathematical approach is to combine precise geometrical models with statistical data analysis tools, thus combining accuracy and robustness.This research will benefit a large number of existing applications and create new ones that rely on efficient object tracking under changing environmental conditions. They include applications in national priority areas like homeland security, monitoring of nuclear installations and border security, in commercial interests like video communications, multimedia databases and entertainment, in social causes like wildlife and environmental monitoring, and in medical and biological applications relying on video analysis. Scene relighting by learning the motion and illumination of objects from natural videos will also have a significant impact in creation of realistic virtual environments.Progress on this project will be regularly updated at http://www.ee.ucr.edu/~amitrc/JMIS.htm