Titlebook: Data Association for Multi-Object Visual Tracking; Margrit Betke,Zheng Wu Book 2017 Springer Nature Switzerland AG 2017

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Classic Batch Data Association Approaches, whenever new data arrives, no matter if they are implemented to solve the association frame by frame or with deferred logic. In contrast, if the entire video can be considered for a tracking task, data association can be operated in batch mode. This has the advantage that association ambiguities ar

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Tracking with Multiple Cameras,ching object measurements obtained at different times. It was assumed that objects are imaged through a single camera, and we relied on the notion of temporal smoothness to handle challenging tracking scenarios, such as occlusions or detector failure. The assumption of temporal smoothness for the mo

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Application to Animal Group Tracking in 3D,ista et al., 2015], fish [Giordano et al., 2016, Lee et al., 2010], and insects [Feldman et al., 2012, Veeraraghavan et al., 2008]. In this chapter, we first describe two systems used for 3D tracking of multiple animals in flight and then give examples of the use of such systems to facilitate resear

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Concluding Remarks,ata association has progressed rapidly in the last thirty years. Classic methods, as described in Chapters 2 and 3, were first developed for radar applications and then revisited in the computer vision domain during the last ten years. Unlike the point measurements in radar scans, the measurements i

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