Foreground segmentation-based human detection with shadow removal

Recent research in video surveillance system has shown an increasing focus on creating reliable systems utilizing non-computationally expensive technique for observing humans' appearance, movements and activities, thus providing analytical information for advanced human behaviour analysis and realistic human modelling. In order for the system to function, it requires robust method for detecting human form from a given input of video streams. In this paper, we present a human detection technique suitable for video surveillance. The technique we propose includes background subtraction, foreground segmentation, and shadow removal. The proposed detection technique will first try to extract all foreground objects from the background and then moving shadows will be eliminated by a shadow detection algorithm. Finally, we perform a morphological reconstruction algorithm to recover the distorted foreground objects after shadow removal process. We define certain features that describe human and match them with the final objects obtained from earlier processing. The experimental result proves its validity and accuracy in various fixed outdoor and indoor video scenes.