Motion Analysis for Scenes with Multiple Moving Objects

概要

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This paper describes an approach for detection and tracking of multiple moving objects in a cluttered environment via tracking of the local image regions. This method is designed to work with image sequences taken from moving cameras. The first image of the sequence is used to compose a triangular grid which vertices are used as feature points. The grid is optimized in order to increase the number of elements in regions with higher level of details. This grid is then used as an initial for the next frame in order to track local features. Neighborhood of each vertex is used to generate color distribution model which is used as a feature vector for tracking. In the second part of the proposed algorithm grids of two consistent frames are used to estimate motion of the correspondent vertices in order to form a motion field. This field is used to find dominant motions and make assumptions for background-foreground motion. The background motion is then used to estimate camera motion parameters. In order to improve robustness of the algorithm context analysis was used. Input images are analyzed to exclude regions bad for tracking (such as trees, road, sky or clouds) from the further processing and verify if moving parts of the scene are more likely to belong to a background or to one of the object class (vehicles, humans, etc).