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Video-Based Face Recognition

tracking module facial features

Definition: Video based face recognition in image sequences has gained increased interest based primarily on the idea expressed by psychophysical studies that motion helps humans recognize faces, especially when spatial image quality is low.

Although face recognition has been an active research topic for decades, the traditional recognition algorithms are all based on static images. However, during the last years face recognition in image sequences has gained increased interest based primarily on the idea expressed by psychophysical studies that motion helps humans recognize faces, especially when spatial image quality is low.

Video-based face recognition systems consist of three modules: a detection module, a tracking module and a recognition module. Given a frame of a video sequence, the detection module locates face candidates, while the tracking module finds the exact position of facial features in the current frame based on an estimate of face or feature locations in the previous frame(s). The recognition module identifies or verifies the face, integrating information from previous frames.

In the detection module, motion and/or skin color information may be used for segmenting the face from the background and locate candidate face regions. Face detection techniques similar to those applied for still images are then employed to find the exact location of faces in the current frame, thus initiating face and facial feature tracking. Face tracking techniques include head tracking, where the head is viewed as a rigid object performing translations and rotations, facial feature tracking, where facial features deformations due to facial expressions or speech are viewed as non rigid transformations limited by the head anatomy, and methods tracking head and features. Face and facial feature tracking is sometimes used to reconstruct the 3D shape of the face, which is subsequently used for enhancing face recognition.

The main problem of video-based face recognition is low quality of images in video sequences, while the unquestionable advantage is the abundance of information. This enables the selection of the frames that will be used for recognition and the reuse of recognition information obtained in precedent frames. Also, temporal continuity allows tracking of facial features, which can help in compensating pose or expression variations, while motion, gait and other features may enhance the performance of face recognition, Moreover, the simultaneous comprehensive exploitation of spatiotemporal cues results in increased tracking and identification accuracy. Video based techniques are ideal for surveillance or facility monitoring applications.

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about 7 years ago

sir/mam,

can u tell me the detail procedure for face recognition in a video clip,with detailed algorithim n codeing.



i am presently working on a project based on face recognition in a video clip.so please kindly help me.



thinking to get reply as soon as possible.