Integrated Facial Feature with Depth Information for Face Recognition

• Main Authors: Wei-han Huang, 黃韋瀚
• Other Authors: Chen-chiung Hsieh
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/60873085984400067643

碩士 === 大同大學 === 資訊工程學系(所) === 100 === In recent years, many face recognition systems were proposed, in which color images were utilized. Due to shadow and light reflection, the recognition rates were reduced. In this paper, depth images captured by Microsoft Kinect camera is used to aid the recognition process by overcoming the effects caused by ambient light and reflection. For both the color image and the depth image produced, three types of facial features are extracted. They are statistics of the gradient direction of facial feature points, signature of facial feature points, and nose profile. All these features are integrated with weights set according to experimental results. Then, Nearest Neighbor Classifier is utilized to do the personal identification. There are 40 persons in the database. A color face image and a complete depth image per person is used for training. We tested five times per person and the recognition rate achieves 98% with execution speed 400ms/frame. However, the recognition rate reduced to 63% under variety of illuminations.