21 May 2015 AESOP: Adaptive Event detection SOftware using Programming by example
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Abstract
This paper presents AESOP, a software tool for automatic event detection in video. AESOP employs a super- vised learning approach for constructing event models, given training examples from different event classes. A trajectory-based formulation is used for modeling events with an aim towards incorporating invariance to changes in the camera location and orientation parameters. The proposed formulation is designed to accommodate events that involve interactions between two or more entities over an extended period of time. AESOP's event models are formulated as HMMs to improve the event detection algorithm's robustness to noise in input data and to achieve computationally efficient algorithms for event model training and event detection. AESOP's performance is demonstrated on a wide range of different scenarios, including stationary camera surveillance and aerial video footage captured in land and maritime environments.
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Ashwin Thangali, Ashwin Thangali, Harsha Prasad, Harsha Prasad, Sai Kethamakka, Sai Kethamakka, David Demirdjian, David Demirdjian, Neal Checka, Neal Checka, "AESOP: Adaptive Event detection SOftware using Programming by example", Proc. SPIE 9473, Geospatial Informatics, Fusion, and Motion Video Analytics V, 947307 (21 May 2015); doi: 10.1117/12.2179194; https://doi.org/10.1117/12.2179194
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