• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.9-16
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• 2002

As existing analog video surveillance systems could save and retrieve data only in a limited space within short distance, it had many constraints in developing into various application systems. However, on the back of development of the Internet and computer technologies, digital video surveillance systems can be controlled from a remote location by web browser without space limits. Moreover, data compression and management technologies with Index Search algorithm make it possible to efficiently handling, storing, and retrieving a large amount of data and further motion detection algorithm enhances a recording speed and efficiency for a practical application, that is, a practical remote recordable video surveillance system using our efficient algorithms as mentioned, called WebCam. The WebCam server system can intelligently record and save video images digitized through efficient database management, monitor and control cameras in a remote place through user authentication, and search logs.

• The Journal of the Acoustical Society of Korea
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• v.30 no.1
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• pp.1-8
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• 2011

This paper presents a method for improving the performance of ISF coefficients quantizer through compensating the defect of the split structure vector quantization using the ordering property of ISF coefficients. And design the ISF coefficients quantizer for wideband speech codec using proposed method. The wideband speech codec uses split structure vector quantizer which could not use the correlation between ISF coefficients fully to reduce complexity and the size of codebook. The proposed algorithm uses the ordering property of ISF coefficients to overcome the defect. Using the ordering property, the codebook redundancy could be figured out. The codebook redundancy is replaced by the adaptive-extended codebook to improve the performance of the quantizer through using the ordering property, ISF coefficient prediction and interpolation of existing codebook. As a result, the proposed algorithm shows that the adaptive-extended codebook algorithm could get about 2 bit gains in comparison with the existing split structure ISF quantizer of AMR-WB (G.722.2) in the points of spectral distortion.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.28-35
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• 2006

Statistical models of shape variability based on active shape models (ASMs) have been successfully utilized to perform segmentation and recognition tasks in two-dimensional (2D) images. Three-dimensional (3D) model-based approaches are more promising than 2D approaches since they can bring in more realistic shape constraints for recognizing and delineating the object boundary. For 3D model-based approaches, however, building the 3D shape model from a training set of segmented instances of an object is a major challenge and currently it remains an open problem in building the 3D shape model, one essential step is to generate a point distribution model (PDM). Corresponding landmarks must be selected in all1 training shapes for generating PDM, and manual determination of landmark correspondences is very time-consuming, tedious, and error-prone. In this paper, we propose a novel automatic method for generating 3D statistical shape models. Given a set of training 3D shapes, we generate a 3D model by 1) building the mean shape fro]n the distance transform of the training shapes, 2) utilizing a tetrahedron method for automatically selecting landmarks on the mean shape, and 3) subsequently propagating these landmarks to each training shape via a distance labeling method. In this paper, we investigate the accuracy and compactness of the 3D model for the human liver built from 50 segmented individual CT data sets. The proposed method is very general without such assumptions and can be applied to other data sets.