Performance evaluation of localized person based scene detection and retrieval in video

In this paper work regarding person localization using novel approach has been carried out. Person localization is the first step in all the surveillance application in multimedia and human-computer interface applications. The objective of this paper is to address a system for a person localization system which describes important tasks of video content analysis, namely, video segmentation, localizing the person and their identification. Video segmentation involves partitioning a video sequence into several smaller meaningful units, based on temporal discontinuities in the video sequence. A novel framework is proposed for combined video segmentation and retrieval of scene with object/person localization. In which the dominant regions as a large area of the frame have been tracked throughout a shot and then stable features are extracted. Dominant region based effective parameters (DREP) model which includes low level features of the proposed model. Here the low level features are referenced as the color of dominant region, edges, area, centroid and position of a particular object or person to be localized in the video. Based on the extracted information dimensional processing is used to extract images of faces or the required objects. The simulated results based on the presented algorithm shows good performance. Also it is highly robust to camera, objects motions and can withstand illumination changes even in different poses in the sequences of the images.