Title :
Robust color histogram descriptors for video segment retrieval and identification
Author :
Ferman, A. Müfit ; Tekalp, A. Murat ; Mehrotra, Rajiv
Author_Institution :
Dept. of Electr. & Comput. Eng., Rochester Univ., NY, USA
fDate :
5/1/2002 12:00:00 AM
Abstract :
Effective and efficient representation of color features of multiple video frames or pictures is an important yet challenging task for visual information management systems. Key frame-based methods to represent the color features of a group of frames (GoF) are highly dependent on the selection criterion of the representative frame(s), and may lead to unreliable results. We present various histogram-based color descriptors to reliably capture and represent the color properties of multiple images or a GoF. One family of such descriptors, called alpha-trimmed average histograms, combine individual frame or image histograms using a specific filtering operation to generate robust color histograms that can eliminate the adverse effects of brightness/color variations, occlusion, and edit effects on the color representation. We show the efficacy of the alpha-trimmed average histograms for video segment retrieval applications, and illustrate how they consistently outperform key frame-based methods. Another color histogram descriptor that we introduce, called the intersection histogram, reflects the number of pixels of a given color that is common to all the frames in the GoF. We employ the intersection histogram to develop a fast and efficient algorithm for identification of the video segment to which a query frame belongs. The proposed color histogram descriptors have been included in the ISO standard MPEG-7 after extensive evaluation experiments.
Keywords :
feature extraction; image colour analysis; image representation; image retrieval; image sequences; statistical analysis; video databases; video signal processing; ISO standard; MPEG-7; alpha-trimmed average histograms; color features representation; color properties; color representation; data structure; efficient algorithm; fast algorithm; group of frames; intersection histogram; key frame-based methods; pixels; query frame; robust color histogram descriptors; selection criterion; video frames; video segment identification; video segment retrieval; video segment retrieval applications; video sequences; visual information management systems; Brightness; Color; Filtering; Histograms; ISO standards; Image databases; Image segmentation; Information management; MPEG 7 Standard; Robustness;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2002.1006397