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Staple: Complementary Learners for Real-Time Tracking
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Figure 1 : Sometimes colour distributions are not enough to discriminate the target from the background. Conversely, template models (like HOG) depend on the spatial configuration of the object and perform poorly when this changes rapidly. Our tracker Staple can rely on the strengths of both template and colour-based models. Like DSST [10], its performance is not affected by non-distinctive colours (top). Like DAT [33], it is robust to fast deformations (bottom). Abstract Correlation
doi:10.1109/cvpr.2016.156
dblp:conf/cvpr/BertinettoVGMT16
fatcat:742ksngrabeqlaje3yh4qrcba4