: Including all the scenes/shots that contain special events may generate too long an abstract. Also, simply staggering them together may not be visually or aurally appealing. In the MoCA project, it was determined that only 50% of the abstract should contain special events. The remaining part should be left for filler clips. The special event clips to be included are chosen uniformly and randomly from different types of events. The selection of a short clip from a scene is subject to some additional criteria, such as the amount of action and the similarity to the overall color composition of the movie. Closeness to the desired AV characteristics of certain scene types are also considered. The filler clips are chosen so that they do not overlap with the content of chosen special event clips, to ensure a good coverage of all parts of a movie. MPEG-7 Standard for Multimedia Content Description Interface MPEG-7 is an on-going standardization effort for content description of AV documen...

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In this paper, a Major Color Spectrum Histogram Representation (MCSHR) is introduced to represent a moving object by using a normalized geometric distance between two points in the RGB space. Then, an Incremental Major Color Representation Algorithm is proposed to cope with small pose changes occurring along the track. Finally, a two directional similarity measurement based on the major colors is used to measure the similarity of any two given moving objects in multiple integrated frames. Experimental results show that with a few (4 or 5) frames MCSHR integration, the proposed Incremental MCSHR algorithm can make matching more robust and reliable than single frame matching, especially for small pose changes. The major color representation algorithm based on the introduced color distance can represent moving objects accurately with a limited number of colors and the frequency of each major color. The similarity of a same moving object in two different tracks has improved from 85 % to 97 % with the number of integrated frames increasing from 1 to 5, while the similarity of two different moving objects has been kept as low as 9 % to 19%. 1.

Abstract. In this paper we present a track matching algorithm based on the “major color ” histograms matching and the post-matching integration useful for tracking a single object across multiple, limitedly disjoint cameras. First, the Major Color Spectrum Histogram (MCSH) is introduced to represent a moving object in a single frame by its most frequent colors only. Then, a twodirectional similarity measurement based on the MCHS is used to measure the similarity of any two given moving objects in single frames. Finally, our track matching algorithm extends the single-frame matching along the objects ’ tracks by a post-matching integration algorithm. Experimental results presented in this paper show the accuracy of the proposed track matching algorithm: the similarity of two tracks from the same moving objects has proved as high as 95%, while the similarity of two tracks from different moving objects has been kept as low as up to 28%. The postmatching integration step proves able to remove detailed errors occurring at the frame level, thus making track matching more robust and reliable. 1

Color and color neighborhood statistics have been used extensively in image matching and retrieval. However, the effective incorporation of color layout information remains a challenging issue. In this paper we present a novel method for color layout based image matching called Spatial Color Component Matching (SCCM). First perceptually dominant colors are extracted from an image and are back-projected to segment the image into various areas. Then, each dominant color area, depending on its size, is segmented into a number of spatial units using a multilevel graph partitioning algorithm. Each unit is described in terms of its color and a set of spatial attributes to form a Spatial Color Component (SCC). All SCC’s form a list that summarizes the color layout information in an image. The distance between two images is then defined by the minimum distance mapping between the two corresponding SCC lists. The algorithm has been evaluated using an image database of wall paper patterns and another database of natural images. It has been judged by human subjects to be highly effective in both cases. 1.

Color is a commonly used feature for realizing content-based image retrieval (CBIR). In this context, this paper presents a new approach for CBIR which is based on well known and widely used color histograms. Contrasting to previous approaches, such as using a single color histogram for the whole image, or local color histograms for a xed number of image cells, the one we propose (named Color-Shape) uses a variable number of histograms, depending only on the actual number of colors present in the image, which our experiments have shown often to be low. Our experiments using a large set of heterogeneous images and pre-defined query/answer sets show that the Color-Shape approach oers good retrieval quality with relatively low space overhead, outperforming previous approaches. Furthermore, we also show that the proposed approach is very flexible in the sense that the user may easily tune it, in order to calibrate the trade-off between space overhead and retrieval effectiveness. F...

In this paper we present a disjoint camera track matching algorithm based on a “cumulative colour histogram transformation”, the “major colour ” histograms matching and the post-matching integration algorithms. In order to reduce the “effects of variable illuminations ” in disjoint camera environment, a cumulative colour histogram transformation is applied to located moving object image first. Then, the Major Colour Spectrum Histogram Representation is introduced to represent a moving object in a single frame by its most frequent colours only. After that, a two-directional similarity measurement based on the MCSHR is proposed to measure the similarity of any two given moving objects in single frames. Finally, our track matching algorithm extends the singleframe matching along the objects ’ tracks by a post-matching integration algorithm. Experimental results presented in this paper show that the unknown illumination effects on moving objects in disjoint camera environment have been reduced significantly by using the proposed cumulative colour histogram transformation algorithm, the proposed similarity measurement algorithm can measure the similarity of the two moving objects accurately, and the post-matching integration proves able to make track matching more robust and reliable.