The Investigation of Clustering Algorithms for Clustering People in Video

• Main Authors: Wei, Liang-You, 魏良佑
• Other Authors: Wang, Tsai-Pei
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/53025973044719030994

碩士 === 國立交通大學 === 多媒體工程研究所 === 100 === 　We investigated clustering algorithm for clustering people in video in this paper. Face image is the most obvious feature of people, but its resolution, luminance, shadow, shooting angle, skin color, and shot, will greatly affect clustering, so we also used the body image and movie time information as the auxiliary. We aggregated the similar people image to the same actor sequence, it can avoid that many disorderly face images reduced performance, and then we computed person similarity matrix between sequences for use. 　Above-mentioned use some objective condition to cluster people, and we also integrated the concept of cluster ensemble, and we tried to cluster the actor sequences. The ensemble similarity matrix is more exquisite than the person similarity matrix. It can help us to realize the similarity between actor sequences. Person similarity matrix and ensemble similarity matrix product their own weight which be computed according to the difference of time, and we sum up the two products of similarity matrix and their own weight, taking it as the final similarity matrix for clustering. We used the final similarity matrix on hierarchical agglomeration to find the final clustering.