• Title/Summary/Keyword: model quantization

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Vector Quantization by N-ary Search of a Codebook (코우드북의 절충탐색에 의한 벡터양자화)

  • Lee, Chang-Young
    • Speech Sciences
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    • v.8 no.3
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    • pp.143-148
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    • 2001
  • We propose a new scheme for VQ codebook search. The procedure is in between the binary-tree-search and full-search and thus might be called N-ary search of a codebook. Through the experiment performed on 7200 frames spoken by 25 speakers, we confirmed that the best codewords as good as by the full-search were obtained at moderate time consumption comparable to the binary-tree-search. In application to speech recognition by HMM/VQ with Bakis model, where appearance of a specific codeword is essential in the parameter training phase, the method proposed here is expected to provide an efficient training procedure.

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Modeling Quantization Error using Laplacian Probability Density function (Laplacian 분포 함수를 이용한 양자화 잡음 모델링)

  • 최지은;이병욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.11A
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    • pp.1957-1962
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    • 2001
  • Image and video compression requires quantization error model of DCT coefficients for post processing, restoration or transcoding. Once DCT coefficients are quantized, it is impossible to recover the original distribution. We assume that the original probability density function (pdf) is the Laplacian function. We calculate the variance of the quantized variable, and estimate the variance of the DCT coefficients. We can confirm that the proposed method enhances the accuracy of the quantization error estimation.

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Compression of 3D Mesh Geometry and Vertex Attributes for Mobile Graphics

  • Lee, Jong-Seok;Choe, Sung-Yul;Lee, Seung-Yong
    • Journal of Computing Science and Engineering
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    • v.4 no.3
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    • pp.207-224
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    • 2010
  • This paper presents a compression scheme for mesh geometry, which is suitable for mobile graphics. The main focus is to enable real-time decoding of compressed vertex positions while providing reasonable compression ratios. Our scheme is based on local quantization of vertex positions with mesh partitioning. To prevent visual seams along the partitioning boundaries, we constrain the locally quantized cells of all mesh partitions to have the same size and aligned local axes. We propose a mesh partitioning algorithm to minimize the size of locally quantized cells, which relates to the distortion of a restored mesh. Vertex coordinates are stored in main memory and transmitted to graphics hardware for rendering in the quantized form, saving memory space and system bus bandwidth. Decoding operation is combined with model geometry transformation, and the only overhead to restore vertex positions is one matrix multiplication for each mesh partition. In our experiments, a 32-bit floating point vertex coordinate is quantized into an 8-bit integer, which is the smallest data size supported in a mobile graphics library. With this setting, the distortions of the restored meshes are comparable to 11-bit global quantization of vertex coordinates. We also apply the proposed approach to compression of vertex attributes, such as vertex normals and texture coordinates, and show that gains similar to vertex geometry can be obtained through local quantization with mesh partitioning.

A Modified Gaussian Model-based Low Complexity Pre-processing Algorithm for H.264 Video Coding Standard (H.264 동영상 표준 부호화 방식을 위한 변형된 가우시안 모델 기반의 저 계산량 전처리 필터)

  • Song, Won-Seon;Hong, Min-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.2C
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    • pp.41-48
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    • 2005
  • In this paper, we present a low complexity modified Gaussian model based pre-processing filter to improve the performance of H.264 compressed video. Video sequence captured by general imaging system represents the degraded version due to the additive noise which decreases coding efficiency and results in unpleasant coding artifacts due to higher frequency components. By incorporating local statistics and quantization parameter into filtering process, the spurious noise is significantly attenuated and coding efficiency is improved for given quantization step size. In addition, in order to reduce the complexity of the pre-processing filter, the simplified local statistics and quantization parameter are introduced. The simulation results show the capability of the proposed algorithm.

Development of Hazardous Food Notification Application Using CNN Model (CNN 모델을 이용한 위해 식품 알림 애플리케이션의 개발)

  • Yoon, Dong Eon;Lee, Hyo Sang;Oh, Am Suk
    • Journal of Korea Multimedia Society
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    • v.25 no.3
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    • pp.461-467
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    • 2022
  • This research is to raise awareness of food safety by designing and supporting a hazard food information notification platform for consumers. To this end, the design was carried out by dividing the process into a data extraction process, an application screen design process, and a CNN-based food inference process. Data was collected through public data APIs and crawling, and it was sent to each activity screen designed for Android studios so that it could be output. As a result, when the platform is executed, information on hazardous food names, registration dates, food classification, manufacturing dates, recovery grades, recovery reasons, recovery methods, company names, barcode numbers, and packaging units can be intuitively and conveniently checked. In addition, CNN-based food inference processes allowed mobile cameras to infer harmful food and applied various quantization techniques such as Dynamic Range, Integer, and Float16 to compare the degree of improvement in inference performance. As a result, the group that applied basic quantization and treated device resources with GPU showed the greatest improvement in inference performance. Through this platform, it is expected that the reliability of food safety will be improved by making it more convenient for consumers to recognize food risks.

Coding Unit-level Multi-loop Encoding Method based on JND for Perceptual Coding (JND 모델을 사용한 코딩 유닛 레벨 멀티-루프 인코딩 기반의 비디오 압축 방법)

  • Lim, Woong;Sim, Donggyu
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.5
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    • pp.147-154
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    • 2015
  • In this paper, we employed a model which defines the sensitivity according to the background luminance, so called JND (Just Noticeable Difference), and applied to the video coding. The proposed method finds out the maximum possible quantization parameter for the current unit based on the threshold of JND model and reduce the bitrate with similar perceptual quality. It selects the higher quantization parameter and reduce the bitrate when the reconstructed signal which is coded with higher quantization parameter is in a range of allowance based on the JND threshold, i.e. the signal has the similar perceptual quality compared to that is coded with the initial quantization parameter. The proposed algorithm was implemented on HM16.0, which is a reference software of the latest video coding standard HEVC (High Efficiency Video Coding) and the coding performance was evaluated. Compared to HM16.0, the proposed algorithm achieved maximum 20.21% and 6.18% of average bitrate reduction with the similar perceptual quality.

3-dimensional Mesh Model Coding Using Predictive Residual Vector Quantization (예측 잉여신호 벡터 양자화를 이용한 3차원 메시 모델 부호화)

  • 최진수;이명호;안치득
    • Journal of Broadcast Engineering
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    • v.2 no.2
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    • pp.136-145
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    • 1997
  • As a 3D mesh model consists of a lot of vertices and polygons and each vertex position is represented by three 32 bit floating-point numbers in a 3D coordinate, the amount of data needed for representing the model is very excessive. Thus, in order to store and/or transmit the 3D model efficiently, a 3D model compression is necessarily required. In this paper, a 3D model compression method using PRVQ (predictive residual vector quantization) is proposed. Its underlying idea is based on the characteristics such as high correlation between the neighboring vertex positions and the vectorial property inherent to a vertex position. Experimental results show that the proposed method obtains higher compression ratio than that of the existing methods and has the advantage of being capable of transmitting the vertex position data progressively.

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MPEG-2 Bit-Rate Control for Video Sequence Editing using Dynamic Macroblock Bit Assignment (압축 비디오시퀀스 편집을 위한 동적 매크로블럭 비트할당 MPEG-2 비트율 제어)

  • Kim, Ju-Do;Lee, Keun-Young
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.9
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    • pp.63-69
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    • 1998
  • In this paper, we propose a new Bit-Rate control algorithm based on bit usage matching to substitute encoded GOP(s) for new GOP(s) in MPEG-2 bitstream. It iteratively encodes current picture according to quantization value of previous picture and records bit-usage of each slice until nearly target bits are used. With target bits falling in two output bits, quantization value of slice should be changed to alleviate output bit error. We use recorded bit-usage information to decide which slices should be encoded with one quantization value and others with another. As every macroblock has different activity, we change macroblock quantization value using slice quantization value and activity value. The simulation results demonstrate that the fluctuation of the output bits can be kept within few-several tens of bits while maintaining the quality of the reconstructed pictures at a relatively stable level.

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Motion Recognition of Smartphone using Sensor Data (센서 정보를 활용한 스마트폰 모션 인식)

  • Lee, Yong Cheol;Lee, Chil Woo
    • Journal of Korea Multimedia Society
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    • v.17 no.12
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    • pp.1437-1445
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    • 2014
  • A smartphone has very limited input methods regardless of its various functions. In this respect, it is one alternative that sensor motion recognition can make intuitive and various user interface. In this paper, we recognize user's motion using acceleration sensor, magnetic field sensor, and gyro sensor in smartphone. We try to reduce sensing error by gradient descent algorithm because in single sensor it is hard to obtain correct data. And we apply vector quantization by conversion of rotation displacement to spherical coordinate system for elevated recognition rate and recognition of small motion. After vector quantization process, we recognize motion using HMM(Hidden Markov Model).

Bearing Fault Diagnosis Using Automaton through Quantization of Vibration Signals (진동신호 양자화에 의한 거동반응을 이용한 베어링 고장진단)

  • Kim, Do-Hyun;Choi, Yeon-Sun
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.16 no.5 s.110
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    • pp.495-502
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    • 2006
  • A fault diagnosis method is developed in this study using automaton through quantization of vibration signals for normal and faulty conditions, respectively. Automaton is a kind of qualitative model which describes the system behaviour at the level of abstraction. The system behavior was extracted from the probability of the output sequence of vibration signals. The sequence was made as vibration levels by reconstructing the originally measured vibration signals. As an example, a fault diagnosis for the bearing of ATM machine was done, which detected the bearing fault with confident level compared to any other existing methods of kurtosis or spectrum analysis.