Imperial College London


Faculty of EngineeringDepartment of Computing

Professor in Machine Learning & Computer Vision



+44 (0)20 7594 8461s.zafeiriou Website CV




375Huxley BuildingSouth Kensington Campus






BibTex format

author = {Chrysos, G and Zafeiriou, SP},
doi = {10.1109/TPAMI.2017.2769654},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
pages = {2555--2568},
title = {PD2T: Person-specific Detection, Deformable Tracking},
url = {},
volume = {40},
year = {2018}

RIS format (EndNote, RefMan)

AB - Face detection/alignment has reached a satisfactory state in static images captured under arbitrary conditions. Such methods typically perform (joint) fitting independently for each frame and are used in commercial applications; however in the majority of the real-world scenarios the dynamic scenes are of interest. Hence, 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\textsuperscript{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\textsuperscript{2}T outperforms all the compared methods.
AU - Chrysos,G
AU - Zafeiriou,SP
DO - 10.1109/TPAMI.2017.2769654
EP - 2568
PY - 2018///
SN - 0162-8828
SP - 2555
TI - PD2T: Person-specific Detection, Deformable Tracking
T2 - IEEE Transactions on Pattern Analysis and Machine Intelligence
UR -
UR -
VL - 40
ER -