Head Pose And Light Source Estimation On Low Resolution Facial Images Using A Texture Based Approach

Kanters, N.B. (2016) Head Pose And Light Source Estimation On Low Resolution Facial Images Using A Texture Based Approach.

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Abstract:Face recognition is a biometric technique with the potential to identify non cooperating human beings in uncontrolled environments. Illumination conditions and head poses are unknown in these situations, causing the performance of state of the art face recognition techniques to drop significantly. An extensively investigated solution for this problem is to transform non frontal facial images into images with a frontal pose, increasing the performance of these FR algorithms. This requires accurate estimation of the head pose. This paper is about a head pose estimation algorithm based on a mathematical model of the human nose. Pixel intensity values, i.e. texture, of the nose region are calculated based on this model. The camera and the light source are modeled at various positions, resulting in a set of pixel vectors. Pixels in the nose region of geometrically normalized probe images are compared with these pixel vectors, after which the head pose and the light source position are estimated. Two different error measures were used. The algorithm shows promising results for head poses within the range of ±15° relative to the frontal view, but performs disappointingly for larger angles. Several improvements are suggested.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:53 electrotechnology
Programme:Electrical Engineering BSc (56953)
Link to this item:http://purl.utwente.nl/essays/71217
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