The Experts below are selected from a list of 72 Experts worldwide ranked by ideXlab platform

Raehong Park - One of the best experts on this subject based on the ideXlab platform.

  • an efficient algorithm for video sequence matching using the modified hausdorff distance and the directed divergence
    IEEE Transactions on Circuits and Systems for Video Technology, 2002
    Co-Authors: Raehong Park
    Abstract:

    To manipulate a large video database, effective video indexing and retrieval are required. A large number of video retrieval algorithms have been presented for framewise user query or video content query, whereas few video-sequence matching algorithms have been investigated. In this paper, we propose an efficient algorithm for video sequence matching using the modified Hausdorff distance and the directed divergence of Histograms between successive frames. To effectively match the video sequences with a low computational load, we use the key frames extracted by the cumulative directed divergence and compare the set of key frames using the modified Hausdorff distance. Experimental results with color video sequences show that the proposed algorithms for video sequence matching yield better performance than conventional algorithms such as Histogram Difference, Histogram intersection, and chi-square test methods.

  • efficient video sequence matching using the cauchy function and the modified hausdorff distance
    Storage and Retrieval for Image and Video Databases, 2001
    Co-Authors: Raehong Park
    Abstract:

    To manipulate large video databases, effective video indexing and retrieval are required. While most algorithms for video retrieval can be commonly used for frame-wise user query or video content query, video sequence matching has not been investigated much. In this paper, we propose an efficient algorithm to match the video sequences using the Cauchy function of Histograms between successive frames and the modified Hausdorff distance. To effectively match the video sequences and to reduce the computational complexity, we use the key frames extracted by the cumulative measure, and compare the set of key frames using the modified Hausdorff distance. Experimental results show that the proposed video sequence matching algorithms using the Cauchy function and the modified Hausdorff distance yield the high accuracy and performances compared with conventional algorithms such as Histogram Difference and directed divergence methods.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Jie Zhao - One of the best experts on this subject based on the ideXlab platform.

  • effective dissolve detection based on accumulating Histogram Difference and the support point
    International Conference on Pervasive Computing, 2010
    Co-Authors: Jianwei Feng, Jie Zhao
    Abstract:

    This paper presents a novel dissolve detection method based on accumulating Histogram Difference (AHD) and support points. The proposed algorithm can detect fades and dissolves and avoid the false detection caused by the flashlight. In terms of recall, precision, computational complexity per frame and computational complexity per pixel, we compare our method with the Twin algorithm and the Two Measures Two Thresholds (TMTT) algorithm for fade detection and dissolve detection. The experimental results demonstrate the superiority of our algorithm

Guizhong Liu - One of the best experts on this subject based on the ideXlab platform.

  • effective fades and flashlight detection based on accumulating Histogram Difference
    IEEE Transactions on Circuits and Systems for Video Technology, 2006
    Co-Authors: Xueming Qian, Guizhong Liu
    Abstract:

    Scene change detection is a fundamental step in automatic video indexing, browsing and retrieval. Fade in and fade out are two kinds of gradually changing scenes which are difficult to be detected in comparison with the abruptly changing scenes. The salient character of flashlight effect is the luminance change, which is caused by abrupt appearance or disappearance of the illumination source. Performance of shot boundary detection is not satisfactory for the video sequences containing flashlights, if no flashlight discrimination strategy is adopted. In this paper, an effective fades and flashlight detection method is proposed for both the compressed and uncompressed videos, based on the accumulating Histogram Difference (AHD). This fades detection method is proposed in terms of their mathematical models. AHDs of all the two consecutive frames during fades transitions can be classified into six cases. The flashlight detection method is proposed based on the AHD and the energy variation characters. AHD and energy variation characters for the starting and ending frames of a flashlight have certain regularities, which can also be expressed by cases. Thus the fades and flashlight detection problems are converted into cases matching ones. Experimental results on several test video sequences with different bit rates show the effectiveness of the proposed AHD based fades and flashlight detection method

Devi J Shree - One of the best experts on this subject based on the ideXlab platform.

  • Histogram Difference with fuzzy rule base modeling for gradual shot boundary detection in video cloud applications
    Cluster Computing, 2019
    Co-Authors: Kethsy A Prabavathy, Devi J Shree
    Abstract:

    In the field of shot boundary detection the fundamental step is video content analysis towards video indexing, summarization and retrieval as to be carried out for video cloud based applications. However, there are several beneficial in the previous work; reliable detection of video shot is still a challenging issue. In this paper the focus is carried out on the problem of gradual transition detection from video. The proposed approach is fuzzy-rule based system with gradual identification and a set of fuzzy rules are evaluated with dissolve and wipes (fad-in and fad-out) during gradual transition. First, extracting the features from the video frames then applying the fuzzy rules in to the frames for identifying the gradual transitions. The main advantage of the proposed method is its level of accuracy in the gradual detection getting increased. Also, the existing gradual detection algorithms are mainly based on the threshold component, but the proposed method is rule based. The proposed method is evaluated on variety of video sequences from different genres and compared with existing techniques from the literature. Experimental results proved for its effectiveness on calculating performance in terms of the precision and recall rates.

Jianwei Feng - One of the best experts on this subject based on the ideXlab platform.

  • effective dissolve detection based on accumulating Histogram Difference and the support point
    International Conference on Pervasive Computing, 2010
    Co-Authors: Jianwei Feng, Jie Zhao
    Abstract:

    This paper presents a novel dissolve detection method based on accumulating Histogram Difference (AHD) and support points. The proposed algorithm can detect fades and dissolves and avoid the false detection caused by the flashlight. In terms of recall, precision, computational complexity per frame and computational complexity per pixel, we compare our method with the Twin algorithm and the Two Measures Two Thresholds (TMTT) algorithm for fade detection and dissolve detection. The experimental results demonstrate the superiority of our algorithm