RI: Medium: Active Scene Interpretation by Entropy Pursuit

该项目开发了一种场景解释的新策略，特别是对来自许多对象类别的实例（例如，厨房场景）和人们在日常生活中与对象交互的视频（例如，烹饪）的混乱场景进行注释。研究小组开发了一个用于场景解释和图像测量的统计模型。该模型的一个组成部分是在一个巨大的解释向量上的先验分布。这个矢量的每个位代表一个具有广泛不同程度的特异性和分辨率的高级场景属性。有些非常粗糙（一般假设），有些非常精细（特定假设）。另一个组件是一个简单的条件数据模型，用于相应的学习二进制分类器族，每个比特一个。然后，通过使用称为？的图像解析算法，以高度从粗到精的方式评估假设，计算场景解释。熵的追求?基于逐步减少不确定性和分类器来检测时空卷中的事件，这些分类器利用了机器学习和动态系统交叉的最新进展。本项目开发的计算模型和场景解析算法广泛适用于许多科学和工程领域的场景解释问题。具体应用包括家庭监控和安全、辅助居家生活、婴幼儿和老人护理等。该项目还为未被充分代表的少数民族的研究生甚至高中生提供研究机会。

This project develops a new strategy for scene interpretation, especially for annotating cluttered scenes with instances from many object categories (e.g., a kitchen scene) and videos of people interacting with objects in everyday life (e.g., cooking). The research team develops a statistical model for scene interpretations and image measurements. One component of the model is a prior distribution on a huge interpretation vector. Each bit of this vector represents a high-level scene attribute with widely varying degrees of specificity and resolution ? some are very coarse (general hypotheses) and some are very fine (specific hypotheses). The other component is a simple conditional data model for a corresponding family of learned binary classifiers, one per bit. The scene interpretation is then computed by assessing hypotheses in a highly coarse-to-fine manner, using an image parsing algorithm called ?entropy pursuit? based on stepwise uncertainty reduction, and classifiers for detecting events in spatiotemporal volumes which leverage on recent advances at the intersection of machine learning and dynamical systems. The computational models and scene parsing algorithms developed in this project are broadly applicable to scene interpretation problems arising in many areas of science and engineering. Specific applications include home surveillance and security, assisted home living, infant and elderly care, etc. The project also provides research opportunities for graduate students in underrepresented minorities and even high school students.