Unsupervised Learning for Incremental 3-D Modeling
نویسندگان
چکیده
Learning based incremental 3D modeling of traffic vehicles from uncalibrated video data stream has enormous application potential in traffic monitoring and intelligent transportation systems. In this paper, video data from a traffic surveillance camera is used to incrementally develop the 3D model of vehicles using a clustering based unsupervised learning. Geometrical relations based on 3D generic vehicle model map 2D features to 3D. The 3D features are then adaptively clustered over the frames to incrementally generate the 3D model of the vehicle. Results are shown for both simulated and real traffic video. They are evaluated by a structural performance measure. Keyword: Incremental Learning, Structural Reliability Measure, 3D Rigid Modeling
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