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A Survey on Moving Object Detection in Static and Dynamic Background for automated video analysis


Ms. Ranjana Shende , G. H. Raisoni Institute of Engineering and Technology For women's, Nagpur, India; Ms. Dipali Shahare, G. H. Raisoni Institute of Engineering and Technology For women's, Nagpur, India


Object Detection, Soft Impute method, Markov Random Field, Temporal Differencing, Moving object extraction, background subtraction.


Detection of moving objects in a video sequence is a difficult task and robust moving object detection in video frames for video surveillance applications is a challenging problem. Object detection is a fundamental step for automated video analysis in many vision applications. Object detection in a video is frequently performed by object detectors or background subtraction techniques. Frequently, an object detector requires manual labeling, while background subtraction needs a training sequence. To automate the analysis, object detection without a separate training phase becomes a critical task. This paper presents a survey of various techniques related to moving object detection and discussed the optimization process that can lead to improved object detection and the speed of formulating the low rank model for detected object.

Other Details

Paper ID: IJSRDV1I10001
Published in: Volume : 1, Issue : 10
Publication Date: 01/01/2014
Page(s): 2050-2054

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