Online multi-face detection and tracking using detector confidence and structured SVMs

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

12 Citations (Scopus)
2 Downloads (Pure)

Abstract

Online detection and tracking of a variable number of faces in video is a crucial component in many real-world applications ranging from video-surveillance to online gaming. In this paper we propose FAST-DT, a fully automated system capable of detecting and tracking a variable number of faces online without relying on any scene-specific cues. FAST-DT integrates a generic face detector with an adaptive structured output SVM tracker and uses the detector's continuous confidence to solve the target creation and removal problem. We improve in recall and precision over a state-of-the-art method on a video dataset of more than two hours while providing in addition an increase in throughput.
Original languageEnglish
Title of host publication2015 12th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 26-28 August 2015, Karlsruhe, Germany
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages1-6
DOIs
Publication statusPublished - Aug 2015

Fingerprint

Dive into the research topics of 'Online multi-face detection and tracking using detector confidence and structured SVMs'. Together they form a unique fingerprint.

Cite this