• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.45-48
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• 2006

This paper presents an approach to visual information based temporal indexing of video sequences. The objective of this work is the integration of an automatic face detection and a matching system for video indexing. The face detection is done using color information. The matching stage is based on the Principal Component Analysis (PCA) followed by the Minimax Probability Machine (MPM). Using PCA one feature vector is calculated for each face which is detected at the previous stage from the video sequence and MPM is applied to these feature vectors for matching with the training faces which are manually indexed after extracting from video sequences. The integration of the two stages gives good results. The rate of 86.3% correctly classified frames shows the efficiency of our system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.122-127
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• 1998

In this paper, we focus on the information retrieval of human individuals who are recorded on the video database. Our purpose is to index persons by their faces or voice and to retrieve their existing time sections on the video data. The database system can track as well as extract a face or voice of a certain person and construct a model of the individual person in self-organization mode. If he appears again at different time, the system can put the mark of the same person to the associated frames. In this way, the same person can be retrieved even if the system does not know his exact name. As the face and speaker modeling, a subspace method is employed to improve the indexing accuracy.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.1050-1060
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• 2011

With increasing need for indexing of persons in a large video database, automatic indexing has been attracting great interest which takes advantage of automatic tagging instead of the time-consuming and costly manual tagging. However, automatic indexing approach should provide a degree of recognition proximity because it cannot identify the persons with accuracy of 100%. In this paper, we propose an efficient storage method for storing posting lists efficiently and a novel ranking technique of ordering relevant videos for efficient retrieval. Through experiment evaluations we have shown that our storage method exhibits good performance in compressing the posting list. We have also shown that the proposed ranking method is effective for finding relevant videos.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10C
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• pp.983-991
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• 2005

Human faces are commonly found in a video such as a drama and provide useful information for video content analysis. Therefore, face detection plays an important role in applications such as face recognition, and face image database management. In this paper, we propose a face detection algorithm based on pre-processing of scene change detection for indexing and cast searching in video. The proposed algorithm consists of three stages: scene change detection stage, face region detection stage, and eyes and mouth detection stage. Experimental results show that the proposed algorithm can detect faces successfully over a wide range of facial variations in scale, rotation, pose, and position, and the performance is improved by $24\%$with profile images comparing with conventional methods using color components.

• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1130-1139
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• 1998

This paper presents an integrated solution for the content-based news video indexing and the retrieval. Currently, it is impossible to automatically index a general video, but we can index a specific structural video such as news videos. Our proposed model extracts automatically the key frames by using the structured knowledge of news and consists of the news item segmentation, caption recognition and search browser modules. We present above three modules in the following: the news event segmentation module recognizes an anchor-person shot based on face recognition, and then its news event are divided by the anchor-person's frame information. The caption recognition module detects the caption-frames with the caption characteristics, extracts their character region by the using split-merge method, and then recognizes characters with OCR software. Finally, the search browser module could make a various of searching mechanism possible.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.417-420
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• 2006

Detection of faces on still color images with arbitrary backgrounds is attempted in this paper. The newly proposed method is invariant to arbitrary background, number of faces, scale, orientation, skin color, and illumination through the steps of color clustering, cluster scanning, sub-block processing, face area detection, and face verification. The sub-block method makes the proposed method invariant to the size and the number of faces in the image. The proposed method does not need any pre-training steps or a preliminary face database. The proposed method may be applied to areas such as security control, video and photo indexing, and other automatic computer vision-related fields.