Bag-of-Words Vector Quantization Based Face Identification

摘要：

This paper investigates the possibility that uses Scale-Invariance Feature Transform (SIFT) feature for face identification. However, it is impossible to employ these SIFT keys,i.e. feature vectors, for identification directly, due to the space incompatible of such SIFT keys. To this end, the Bag-of-words(Bow) vector quantization introduced from scene or text classification is conducted for unifying them. And a novel distance, Cauchy-Schwartz Inequality Distance (CSID), is performed for determining which cluster each keypoint of image belongs to after quantization, in order to compose a histogram vector as our feature. To summarize, this approach solves the problem of space incompatible and avoids a high computation that gives rises to a dimensional curse.The experiment shows a reasonable result using SVM classifier by ORL database.

作者: Di Liu Dong-mei Sun Zheng-ding Qiu

作者单位: Institute of Information Science Beijing Jiaotong University Beijing, China

会议类型: 国际会议

会议名称: Second International Symposium on Electronic Commerce and Security(第二届电子商务与安全国际研究大会)(ISECS 2009)

会议地点: 南昌

会议语种:英文

页码: 685-689

在线出版日期: 2009-05-22（万方平台首次上网日期，不代表论文的发表时间）