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Automatic Reasoning about Causal Events in Surveillance Video
2011
EURASIP Journal on Image and Video Processing
We present a new method for explaining causal interactions among people in video. The input to the overall system is video in which people are low/medium resolution. We extract and maintain a set of qualitative descriptions of single-person activity using the low-level vision techniques of spatiotemporal action recognition and gaze-direction approximation. This models the input to the "sensors" of the person agent in the scene and is a general sensing strategy for a person agent in a variety of
doi:10.1155/2011/530325
fatcat:v6gt42qhlrgnzbdlq7nuodrbnq