• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.98-106
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• 2013

In this paper, we propose a moving object detection and tracking method for multi-view camera environment. Based on the similarity and characteristics of motion vectors and coding block modes extracted from compressed bitstreams, validation of moving blocks, labeling of the validated blocks, and merging of neighboring blobs are performed. To continuously track objects for temporary stop, crossing, and overlapping events, a window based object updating algorithm is proposed for single- and multi-view environments. Object detection and tracking could be performed with an acceptable level of performance without decoding of video bitstreams for normal, temporary stop, crossing, and overlapping cases. The rates of detection and tracking are over 89% and 84% in multi-view environment, respectively. The rates for multi-view environment are improved by 6% and 7% compared to those of single-view environment.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.407-419
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• 2006

In this paper, an adaptive illumination change compensation method is proposed for multi-view video coding. In multi-view video, an illumination change can occur due to physically imperfect camera calibration, each different camera position and direction, and so on. These characteristics can cause a performance decrease in the multi-view video coding that uses an inter-view prediction by referring to the pictures obtained from the neighboring views. By using the proposed method, a compression ratio of the proposed method in the multi-view video coding is increased, and finally $0.1{\sim}0.6dB$ PSNR(Peak Signal-to-Noise Ratio) improvement was obtained compared with the case of not using the proposed method.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.586-595
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• 2008

In this paper, we propose an adaptive multi-view video service framework suitable for mobile environments. The proposed framework generates intermediate views in near-realtime and overcomes the limitations of mobile services by adapting the multi-view video according to the processing capability of a mobile device as well as the user characteristics of a client. By implementing the most of adaptation processes at the server side, the load on a client can be reduced. H.264/AVC is adopted as a compression scheme. The framework could provide an interactive service with efficient video service to a mobile client. For this, we present a multi-view video DIA (Digital Item Adaptation) that adapts the multi-view video according to the MPEG-21 DIA multimedia framework. Experimental results show that our proposed system can support a frame rate of 13 fps for 320{\times}240 video and reduce the time of generating an intermediate view by 20 % compared with a conventional 3D projection method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1833-1848
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• 2022

Named entity recognition (NER) is an important basic task in the field of Natural Language Processing (NLP). Recently deep learning approaches by extracting word segmentation or character features have been proved to be effective for Chinese Named Entity Recognition (CNER). However, since this method of extracting features only focuses on extracting some of the features, it lacks textual information mining from multiple perspectives and dimensions, resulting in the model not being able to fully capture semantic features. To tackle this problem, we propose a novel Multi-view Semantic Feature Fusion Model (MSFM). The proposed model mainly consists of two core components, that is, Multi-view Semantic Feature Fusion Embedding Module (MFEM) and Multi-head Self-Attention Mechanism Module (MSAM). Specifically, the MFEM extracts character features, word boundary features, radical features, and pinyin features of Chinese characters. The acquired font shape, font sound, and font meaning features are fused to enhance the semantic information of Chinese characters with different granularities. Moreover, the MSAM is used to capture the dependencies between characters in a multi-dimensional subspace to better understand the semantic features of the context. Extensive experimental results on four benchmark datasets show that our method improves the overall performance of the CNER model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.53-59
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• 2009

Multi-view video is necessary to develop a new compression encoding technique for storage and transmission, because of a huge amount of data. Layered depth image is an efficient representation method of multi-view video data. This method makes a data structure that is synthesis of multi-view color and depth image. This paper proposed enhanced compression method by presentation of efficient layered depth image using real distance comparison, solution of overlap problem, and interpolation. In experimental results, confirmed high compression performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2720-2736
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• 2013

Multi-view face detection has become an active area for research in the last few years. In this paper, a novel multi-view human face detection algorithm based on improved real Adaboost is presented. Real Adaboost algorithm is improved by weighted combination of weak classifiers and the approximately best combination coefficients are obtained. After that, we proved that the function of sample weight adjusting method and weak classifier training method is to guarantee the independence of weak classifiers. A coarse-to-fine hierarchical face detector combining the high efficiency of Haar feature with pose estimation phase based on our real Adaboost algorithm is proposed. This algorithm reduces training time cost greatly compared with classical real Adaboost algorithm. In addition, it speeds up strong classifier converging and reduces the number of weak classifiers. For frontal face detection, the experiments on MIT+CMU frontal face test set result a 96.4% correct rate with 528 false alarms; for multi-view face in real time test set result a 94.7 % correct rate. The experimental results verified the effectiveness of the proposed approach.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.43-51
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• 2014

Multi-view video including depth image is necessary to develop a new compression encoding technique for storage and transmission, because of a huge amount of data. Layered depth image is an efficient representation method of multi-view video data. This method makes a data structure that is synthesis of multi-view color and depth image. This efficient method to compress new contents is suggested to use layered depth image representation and to apply for video compression encoding by using 3D warping. This paper proposed enhanced compression method using layered depth image representation and H.264/AVC video coding technology. In experimental results, we confirmed high compression performance and good quality of reconstructed image.

• Journal of Broadcast Engineering
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• v.20 no.6
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• pp.921-927
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• 2015

In this paper, we propose a novel design scheme for the operation of Decoded Picture Buffer (DPB) including reference picture re-ordering, marking process, and reference picture list construction to perform an efficient scalable multi-view video coding. Extensive simulations show that the proposed method can provide improved compression efficiency and improved video quality measured in terms of BD-Rate and BD-PSNR for the scalable multi-view video coding.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2005.11a
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• pp.209-212
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• 2005

This paper introduces interactive multi-view contents authoring system based on MPEG-4. The MPEG-4 standard, which aims to provide an object based audiovisual coding tool, has been developed to address the emerging needs from communications, interactive broadcasting as well as from mixed service models resulting from technological convergence. Due to the feature of object based coding, it has been considered that MPEG-4 is the most suitable for interactive broadcasting content production. This feature is suitable for creation of the content which provides multiple views of object or scene in interactive manner. In this paper, we categorize the multi-view visual content into two types: panoramic multi-view content and object multi-view content. And design and implementation of the authoring system for interactive multi-view contents is presented. We believe that the proposed method can be effectively used for further deployment of MPEG-4 content to various interactive applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.186-193
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• 2009

Multi-view video is necessary to develop a new compression encoding technique for storage and transmission, because of a huge amount of data. Layered depth image is an efficient representation method of multi-view video data. This method makes a data structure that is synthesis of multi-view color and depth image. This paper proposed enhanced compression method by presentation of efficient layered depth image using real distance comparison, solution of overlap problem, and YCrCb color transformation. In experimental results, confirmed high compression performance and good reconstructed image.