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Multi-view Face Detection with One Classifier for Video Analytics Systems
Date
2014-08-24
Author
Kaya, Tunç Güven
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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In a video analytics for audience measurement system, dwell time, gaze, and opportunity-to-see statistics are required most of the time. To generate these statistics, more than one face detector is used in order to capture both profile and frontal faces. In this paper, we present a novel approach for face detection in video analytics. The assumption is that; the face occurrences are limited in such systems and one classifier is able to capture all of these occurrences. By using MB-LBP for feature extraction and Gentle Boost for statistical learning we trained a classifier which is able to detect both profiles and frontal faces with more than 80 % success rate. The proposed system also uses an efficient scanning algorithm and achieves 60 fps on a 720p video.
Subject Keywords
Multi-view face detection
,
Object detection
,
Audience measurement system
,
Multi-block lbp
,
Video analytics
URI
https://hdl.handle.net/11511/32354
DOI
https://doi.org/10.1007/978-3-319-12811-5_7
Collections
Graduate School of Informatics, Conference / Seminar
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T. G. Kaya, “Multi-view Face Detection with One Classifier for Video Analytics Systems,” 2014, vol. 8811, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32354.