PD2T : person-specific detection, deformable tracking
Chrysos, Grigorios G.; Zafeiriou, Stefanos (2017-11-03)
G. G. Chrysos and S. Zafeiriou, "PD2T: Person-Specific Detection, Deformable Tracking," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 11, pp. 2555-2568, 1 Nov. 2018. doi: 10.1109/TPAMI.2017.2769654
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https://urn.fi/URN:NBN:fi-fe201902276473
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Abstract
Face detection/alignment methods have reached a satisfactory state in static images captured under arbitrary conditions. Such methods typically perform (joint) fitting for each frame and are used in commercial applications; however in the majority of the real-world scenarios the dynamic scenes are of interest. We argue that generic fitting per frame is suboptimal (it discards the informative correlation of sequential frames) and propose to learn person-specific statistics from the video to improve the generic results. To that end, we introduce a meticulously studied pipeline, which we name PD 2 T, that performs person-specific detection and landmark localisation. We carry out extensive experimentation with a diverse set of i) generic fitting results, ii) different objects (human faces, animal faces) that illustrate the powerful properties of our proposed pipeline and experimentally verify that PD 2 T outperforms all the compared methods.
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