TY - GEN
T1 - Multi-pose face recognition for person retrieval in camera networks
AU - Bäuml, Martin
AU - Bernardin, Keni
AU - Fischer, Mika
AU - Ekenel, Hazim Kemal
AU - Stiefelhagen, Rainer
PY - 2010
Y1 - 2010
N2 - In this paper, we study the use of facial appearance features for the re-identification of persons using distributed camera networks in a realistic surveillance scenario. In contrast to features commonly used for person reidentification, such as whole body appearance, facial features offer the advantage of remaining stable over much larger intervals of time. The challenge in using faces for such applications, apart from low captured face resolutions, is that their appearance across camera sightings is largely influenced by lighting and viewing pose. Here, a number of techniques to address these problems are presented and evaluated on a database of surveillance-type recordings. A system for online capture and interactive retrieval is presented that allows to search for sightings of particular persons in the video database. Evaluation results are presented on surveillance data recorded with four cameras over several days. A mean average precision of 0.60 was achieved for inter-camera retrieval using just a single track as query set, and up to 0.86 after relevance feedback by an operator.
AB - In this paper, we study the use of facial appearance features for the re-identification of persons using distributed camera networks in a realistic surveillance scenario. In contrast to features commonly used for person reidentification, such as whole body appearance, facial features offer the advantage of remaining stable over much larger intervals of time. The challenge in using faces for such applications, apart from low captured face resolutions, is that their appearance across camera sightings is largely influenced by lighting and viewing pose. Here, a number of techniques to address these problems are presented and evaluated on a database of surveillance-type recordings. A system for online capture and interactive retrieval is presented that allows to search for sightings of particular persons in the video database. Evaluation results are presented on surveillance data recorded with four cameras over several days. A mean average precision of 0.60 was achieved for inter-camera retrieval using just a single track as query set, and up to 0.86 after relevance feedback by an operator.
UR - http://www.scopus.com/inward/record.url?scp=78449298189&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78449298189&partnerID=8YFLogxK
U2 - 10.1109/AVSS.2010.42
DO - 10.1109/AVSS.2010.42
M3 - Conference contribution
AN - SCOPUS:78449298189
SN - 9780769542645
T3 - Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010
SP - 441
EP - 447
BT - Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010
PB - IEEE Computer Society
T2 - 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010
Y2 - 29 August 2010 through 1 September 2010
ER -