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Processing of image sequences has progressed from simple structure from motion paradigm to the recognition of actions/interactions as events. Understanding human activities in video has many potential applications including automated surveillance, video archival/retrieval, medical diagnosis, sports analysis, and human-computer interaction. Understanding human activities involves various steps of low-level vision processing such as segmentation, tracking, pose recovery, and trajectory estimation as well as high-level processing tasks such as body modeling and representation of action. While low-level processing has been actively studied, high-level processing is just beginning to receive attention. This is partly because high-level processing depends on the results of low-level processing. However, high-level processing also requires some independent and additional approaches and methodologies. We focus on the following aspects of high-level processing: (1) human body modeling, (2) level of detail needed to understand human actions, (3) approaches to human action recognition, and (4) high-level recognition schemes with domain knowledge. The review is illustrated by examples of each of the areas discussed, including recent developments in our work on understanding human activities.
Aggarwal et al. (Mon,) studied this question.