A simplified ordinal-based method for video signature

Chaisorn, Lekha; Manders, Corey

doi:10.1109/icics.2009.5397482

Cited by 5 publications

(10 citation statements)

References 12 publications

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“…More detail on this algorithm may be found in [3]. Figure 2 illustrates the construction of a meta-slice.…”

Section: ) For An Entrymentioning

confidence: 99%

“…The first process in [2] is to divide each keyframe (converted to a gray scale image and downsized if necessary) into blocks {Bl' B2, ... , Bm}, where m is the number of blocks in a keyframe. For each block Bk, where k = I to m, the metaslice Mk is then generated based on the algorithm presented in [3]. Details of the algorithm which generates the meta-slices Mk for each block B k are presented below.…”

Section: A Video Processingmentioning

confidence: 99%

“…hue and saturation color segmentation method described in [3]. Second, each shot is processed to select its keyframes.…”

Section: A Video Processingmentioning

confidence: 99%

“…This work is built on our earlier work in [3]. In this system, we first extract the keyframes of each video.…”

Section: Introductionmentioning

confidence: 99%

“…As video is rich in visual as well as semantic content, video search remains challenging. In the area of copy detection, previous studies have shown that ordinal representations are robust to several transformations [2], [3] such as color change, brightness change, and the addition of Gaussian noise. However, for the case where a logo, text captions or an original video is within a suspect video, these methods tend to fail to detect.…”

Section: Introductionmentioning

confidence: 99%

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A bitmap indexing approach for video signature and copy detection

Chaisorn

Sainui

Mander

2010

2010 5th IEEE Conference on Industrial Electronics and Applications

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In this paper, a framework for video signature indexing and copy detection incorporating a bitmap structure is proposed. The work we present improves the computational time during the detection process of video matching, as well as reducing the space needed to store the video signatures. In addition, the method improves the detection in the case where a caption or logo has been inserted into the original video.The proposed framework is composed of two levels of bitmap indexing. The first level reduces the time taken for performing video matching between a query video and videos in the database. This can be achieved by grouping videos (keyframes) into clusters and using them as the first level index. During the video matching process, this index is used to determine the relevant clusters, so that the video in question need only be matched with those clusters, rather than the entire database, significantly reducing the computational time. The second level index reduces the space required to store the video signatures. This is achieved by converting the video signatures into bitmap vectors. In addition, another advantage of adopting a bitmap indexing method is that a low-cost Boolean operation such as AND, OR, and XOR can be utilized in the analysis. This two-level indexing scheme is simple but efficient and improves the overall system performance.

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“…More detail on this algorithm may be found in [3]. Figure 2 illustrates the construction of a meta-slice.…”

Section: ) For An Entrymentioning

confidence: 99%

Section: A Video Processingmentioning

confidence: 99%

“…hue and saturation color segmentation method described in [3]. Second, each shot is processed to select its keyframes.…”

Section: A Video Processingmentioning

confidence: 99%

“…This work is built on our earlier work in [3]. In this system, we first extract the keyframes of each video.…”

Section: Introductionmentioning

confidence: 99%