Video Indexing and Retrieval

Thanks to technological advancements in image/video capturing, data storage, compression, personal computing, and networking, an eve-growing amount of digital images and videos are becoming accessible to the general user. To take advantage of the rich information content of these media, data management systems that allow efficient and effective storage, indexing, and retrieval of these data are essential. Conventional data management systems, which excel in dealing with alphanumeric data, do not handle image/video data well. To accommodate these multimedia data, researchers have suggested the content/based indexing and retrieval paradigm. In this chapter, we describe the computation of different image and video features that researchers proposed to characterize the contents of images/videos and to allow efficient indexing and retrieval. In particular, we describe the computation and use of low-level features such as color, texture, shape, and motion, as well as high-level features such as human faces. Empirical results and prototypes are illustrated to show the effectiveness of these features. Limitations and tradeoffs of different features are discussed.