  In this paper, we introduce a framework for classifying images according to
high-level sentiment. We subdivide the task into three primary problems:
emotion classification on faces, human pose estimation, and 3D estimation and
clustering of groups of people. We introduce novel algorithms for matching body
parts to a common individual and clustering people in images based on physical
location and orientation. Our results outperform several baseline approaches.
