SPR 2018 - Semantic Person Retrieval in Surveillance Using Soft Biometrics

In surveillance and security today it is a common goal to locate a subject of interest purely from a semantic description; think an offender description form handed into a law enforcement agency. To date, these tasks are primarily undertaken by operators on the ground either by manually searching a premises or by combing through hours of video footage. As such, the Australian Federal Police identified this area as a significant problem within law enforcement. To date, researchers have focused on person re-identification methodologies to solve this complex problem, however, in circumstances where pre-search subject enrollment images are not available, these techniques fail.
Semantic search is of primary interest as it does not require pre-search subject enrollment and instead searches video footage based on a textually supplied target query. The aim of this challenge is to attempt to solve this problem through two tasks, each of these tasks aims to locate a subject of interest based on a soft biometric signature.
Website: https://semanticsbsearch.wordpress.com/
Organisers:
Michael Halstead (Queensland University of Technology, Australia)
Simon Denman (Queensland University of Technology, Australia)
Clinton Fookes (Queensland University of Technology, Australia)
YingLi Tian (The City University of New York, USA)
Mark S. NIxon (University of Southampton, UK)