FACE VERIFICATION USING D-HMM AND ADAPTIVE K-MEANS CLUSTERING

摘要：

In this paper, we propose a pseudo 2 Dimension Discrete HMM (P2D-DHMM) for face verification. Each face image is scanned for frontal face in two ways. One way from top to bottom and one way from right to left by a sliding window and two set features are extracted. 2D-DCT coefficients as features are extracted. K-means clustering is used for generation two codebook and then by the vector quantization (VQ) two code words for each face image are generated. These code words are used as observation vectors in training and recognition phase. Two separate Discrete HMM (each HMM for each way) is trained by Baum Welch algorithm for each set of containing image of the same face ( λv c,λh c ). A test face image is recognized by finding the best match (likelihood) between the image and all of the HMMs ( λv c+λh c ) face models using forward algorithm. Experimental results show the advantages of using P2D-DHMM recognizer engine instead of conventional continues HMM.

作者: Behrouz Vaseghi Somayeh Hashemi

作者单位: Islamic Azad University, Abhar branch, Iran

会议类型: 国际会议

会议名称: 2011 4th IEEE International Conference on Broadband Network & Multimedia Technology(第四届IEEE宽带网络与多媒体国际会议 4th IEEE IC-BNMT2011)

会议地点: 深圳

会议语种:英文

页码: 270-275

在线出版日期: 2011-10-28（万方平台首次上网日期，不代表论文的发表时间）