Model-Based Pedestrian Segmentation
نویسنده
چکیده
The Problem: Many video-surveillance applications involve video data of humans in scenes. To accurately describe the location, action, and appearance of humans under video surveillance, we need to segment the people from the scene. We propose to use a model-based approach to segment humans from the scene. We are in particular interested in pedestrians from video data. A good segmentation will allow us to estimate accurately the limb sizes, posture, and orientations, making possible applications such as identification of people by their walking appearance, and understanding human activities on an individual level.
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تاریخ انتشار 2002