A study on various face detection techniques in real time video environment

Day to day the increases in the use of social networking sites like Facebook, twitter, Instagram etc. so most of the peoples are shearing the 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 important applications. In this paper, we will introduce the face image retrieval technique from the video frames. Our aim is to detect human attributes automatically which contain semantic cues of face photos to improve content base face retrieval. 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 and online stages. The result shows that the face images which is occurs in the video and match with our face database.