Video background retrieval using mosaic images

Content-based video retrieval is one of the most active and exciting research areas in the field of multimedia technology. In this paper, we present an approach for video background retrieval using mosaic images and a support vector machine (SVM). The video is captured by a moving camera and a portion of the scene is visible at any time. The Kanade-Lucas-Tomasi (KLT) feature tracker is used to get the correspondences between consecutive images and the homography is calculated using these correspondences. We use the homography to construct the mosaic background image and a mixture of Gaussian (MoG) background subtraction algorithm to remove the moving objects in the scene. An SVM is then applied to classify the mosaic background image. The experimental results show the efficiency and effectiveness of the proposed approach.