Face processing techniques for automatic recognition in broadcast video attract the research interest because of its value in applications, such as video indexing, retrieval, and summarization. In multimedia press review, the automatic annotation of broadcasting news programs is a challenging task because people can appear with large appearance variations such as hair styles, illumination conditions and poses that make the comparison between similar faces more difficult. In this paper a technique for automatic face identification in TV broadcasting programs based on a gallery of faces downloaded from Web is proposed. The approach is based on a joint use of Scale Invariant Feature Transform descriptor and Eigenfaces-based algorithms and it has been tested on video sequences using a database of images acquired starting from a web search. Experimental results show that the joint use of these two approaches improves the recognition rate in case of use Standard Definition (SD) and High Definition (HD) standards.
The automatic labeling of faces in TV broadcasting is still a challenging problem. The high variability in view points, facial expressions,
general appearance, and lighting conditions, as well as occlusions, rapid shot changes, and camera motions, produce
significant variations in image appearance. The application of automatic tools for face recognition is not yet fully established
and the human intervention is needed. In this paper, we deal with the automatic face recognition in TV broadcasting programs.
The target of the proposed method is to identify the presence of a specific person in a video by means of a set of images
downloaded from Web using a specific search key.
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