The enhancement of digital devices and the popularity of social networking sites like Facebook, twitter, Instagram etc. The large numbers of peoples are shearing their images and videos by different social networking sites. The users are very much interested in uploading the images or videos on the internet in which most of the photos and videos contain faces. Thus with the rapidly growing photos and videos on the internet the large scale content base face image retrieval is a facilitating technology for many prominent applications. In this project, our aim is to detect a human face image which is present in the video frame and retrieving the similar human face images from the large scale database. By using human attributes in a systematic and scalable framework. The attribute-enhanced sparse coding is used to improve the performance of face retrieval in the offline stage. With this method the performance improvement to greater extent. Experimenting on public photo and video datasets, the result shows that the implementation of above method by using video.

Face image, human attributes, content-based image retrieval, Face image retrieval, Face occurrences in videos

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