Object recognition for video retrieval

Abstract

Recognition of objects in video can offer significant benefits to video retrieval including automatic annotation and content based queries based on the object characteristics. This paper describes our preliminary work toward recognizing objects in video sequences and gives a brief survey of the relevant research in the literature. We use the Kalman filter to obtain segmented blobs from the video, classify the blobs using the probability ratio test, and apply several different temporal filtering methods, which results in sequential classification methods over the video sequence containing the blob. Results from real video sequences are shown.