Abstract
Optical Flow is the apparent motion of pixels that is generated when there is relative motion between an observer and a scene. Optical flow is used in many areas of research for object detection, motion estimation, navigation and tracking applications. In this paper, we have proposed two novel applications where Optical Flow has been used for Determining Shot Transitions in a video sequence and Human-Face Expression Detection in a video. For Video Shot Detection, local invariant feature points using SIFT (Scale Invariant Feature Transform) corner detectors is calculated and Optical Flow is computed with the detected feature points to determine shot changes in the video. Quality Parameters like Recall, Precision and F-measure is used to determine the quality of the algorithm. Whereas for detecting of human faces, we begin by first performing skin segmentation to obtain probable regions where human face is present. Within the probable region Optical Flow is used to eliminate the background and other objects having human skin color. From the isolated face, Optical Flow is used for identifying expressions.
Published Version
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