Fast head-shoulder detection on mobile phones

Numerous digital cameras and modern phones have a face detection module, which is used to automatically focus (AF) and optimize exposure (AE). But the face detection will fail when person doesn't face the camera or the part of the face is occluded. In order to avoid such problems, we propose a...

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Bibliographic Details
Published in2011 IEEE International Conference on Consumer Electronics (ICCE) pp. 205 - 206
Main Authors Jun-Qiang Wang, Hua-Dong Ma, An-Long Ming
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2011
Subjects
Cameras
Detectors
Face
Face detection
Histograms
Mobile handsets
Support vector machines
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Summary:Numerous digital cameras and modern phones have a face detection module, which is used to automatically focus (AF) and optimize exposure (AE). But the face detection will fail when person doesn't face the camera or the part of the face is occluded. In order to avoid such problems, we propose a fast head-shoulder detector, which uses Variable-size block Histograms of Orientated Gradients (VHOG) descriptors. AdaBoost-based feature selection algorithm and integral image representation are used to speed up the algorithm. The tests reveal that the method shows very good results and works efficiently in spite of the low computational power and memory available in mobile devices.
ISBN:9781424487110
1424487110
ISSN:2158-3994
2158-4001
DOI:10.1109/ICCE.2011.5722542