HUMAN IDENTIFY IN A VIDEO SEQUENCE USING AN ADVANCED LEARNING APPROACH

Nowadays, monitoring using a surveillance camera is the main challenging task. In this regard, human detection in video sequences is one of the challenging approaches. In a variety of real-world applications, human identification in videos (i.e., a sequence of images) is critical (e.g., visual surveillance and automated driver assistance). In this work, we are using a sliding window algorithm to detect a human in the video frame sequences. Hence false positive is another challenging task. Extensive work is carried out to reduce the false positive of this work to make it applicable in a real-world scenario.