Human Segmentation Using Haar-Classifier

Segmentation is an important process in many aspects of multimedia applications. Fast and perfect segmentation of moving objects in video sequences is a basic task in many computer visions and video investigation applications. Particularly Human detection is an active research area in computer vision applications. Segmentation is very useful for tracking and recognition the object in a moving clip. The motion segmentation problem is studied and reviewed the most important techniques. We illustrate some common methods for segmenting the moving objects including background subtraction, temporal segmentation and edge detection. Contour and threshold are common methods for segmenting the objects in moving clip. These methods are widely exploited for moving object segmentation in many video surveillance applications, such as traffic monitoring, human motion capture. In this paper, Haar Classifier is used to detect humans in a moving video clip some features like face detection, eye detection, full body, upper body and lower body detection.