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Head pose estimation using KNN based image reconstruction

Credit to Download: 1 | Page Numbers 6 | Abstract Views: 98
Year: 2016
COI code: COMCONF04_112
Paper Language: English

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Authors Head pose estimation using KNN based image reconstruction

  Ali Farahani - Department of Computer Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
  Hadis Mohseni - Young Researchers Society, Shahid Bahonar University of Kerman, Kerman, Iran


Head pose estimation is a challenging task for many computer vision systems, such as face detection and face recognition. In recent years, several methods have been proposed for head pose estimation. However, most of the proposed methods in this area are based on facial feature detection and location of facial features such as eyes and nose tip is necessary for accurate head pose estimation in them. Although some of these methods have perfect performance for small and medium (about ±45°) head pose angles, uncontrolled conditions such as illumination and occlusion can affect the facial feature detection and pose estimation performance. In this paper, we propose a holistic pose estimation method with low computational cost which is based on linear reconstruction of a face image over its nearest neighbors in training images, regardless of facial feature locations. The proposed method benefits from the assumption that the reconstruction of a face image in an arbitrary pose p from training images in pose p has less error than the reconstruction of that image from training images in other poses. Extensive experiments are conducted on FacePix and CMU-PIE face databases to verify the efficacy and accuracy of the proposed method


head pose estimation, linear reconstruction, nearest neighbors

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COI code: COMCONF04_112

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Farahani, Ali & Hadis Mohseni, 2016, Head pose estimation using KNN based image reconstruction, 4th International Conference on Electrical and Computer Engineering, تهران , موسسه آموزش عالي صالحان, دانشكده مديريت دانشگاه تهران, the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
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The University/Research Center Information:
Type: state university
Paper No.: 14001
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