NON-RIGID MULTI-BODY TRACKING IN RGBD STREAMS

Dai, K. X.; Guo, H.; Mordohai, P.; Marinello, F.; Pezzuolo, A.; Feng, Q. L.; Niu, Q. D.

To efficiently collect training data for an off-the-shelf object detector, we consider the problem of segmenting and tracking non-rigid objects from RGBD sequences by introducing the spatio-temporal matrix with very few assumptions – no prior object model and no stationary sensor. Spatial temporal matrix is able to encode not only spatial associations between multiple objects, but also component-level spatio temporal associations that allow the correction of falsely segmented objects in the presence of various types of interaction among multiple objects. Extensive experiments over complex human/animal body motions with occlusions and body part motions demonstrate that our approach substantially improves tracking robustness and segmentation accuracy.

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Zitierform:

Dai, K. X. / Guo, H. / Mordohai, P. / et al: NON-RIGID MULTI-BODY TRACKING IN RGBD STREAMS. 2019. Copernicus Publications.

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Rechteinhaber: K. X. Dai et al.

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