Paper
19 June 2017 Upright detection of in-plain rotated face images with complicated background for organizing photos
Author Affiliations +
Proceedings Volume 10443, Second International Workshop on Pattern Recognition; 104430L (2017) https://doi.org/10.1117/12.2280251
Event: Second International Workshop on Pattern Recognition, 2017, Singapore, Singapore
Abstract
Digital cameras and smart-phones with orientation sensors allow auto-rotation of portrait images. Auto-rotation of portrait is done by using the image file's metadata, exchangeable image file format (EXIF). The output of these sensors is used to set the EXIF orientation flag to reflect the positioning of the camera with respect to the ground. Unfortunately, software program support for this feature is not widespread or consistently applied. Our research goal is to create the EXIF orientation flag by detecting the upright direction of face images having no orientation flag and is to apply the software of organizing photos. In this paper, we propose a novel upright detection scheme for face images that relies on generation of rotated images in four direction and part-based face detection with Haar-like features. Inputted images are frontal faces and these images are in-plain rotated in four possible direction. The process of upright detection is that among four possible rotated images, if only one rotated image is accepted in face detection and other three rotated images are rejected, the upright direction is obtained from the accepted direction. Rotation angle of EXIF orientation is, 0 degree, 90 degree clockwise, 90 degree counter-clockwise, or 180 degree. Experimental results on 450 face image samples show that proposed method is very effective in detecting upright of face images with background variations.
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Yoshihiro Shima "Upright detection of in-plain rotated face images with complicated background for organizing photos", Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104430L (19 June 2017); https://doi.org/10.1117/12.2280251
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Facial recognition systems

Image processing

Sensors

Applied research

Cameras

Digital cameras

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