• Title/Summary/Keyword: model quantization

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Adaptive rate control for video communication (동영상 통신을 위한 적응 비트율 제어)

  • 김학수;정연식
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.9A
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    • pp.1383-1391
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    • 1999
  • This paper presents a rate control method that minimizes global distortion under given target bit rates for video communication. This method makes the quality of reconstructed images better than that of the conventional ones based on R-D model at the same bit rates. Given a set of quantizers, a sequence of macroblocks to be quantized selects the optimal quantizer for each macroblock so that the total cost measure is minimized and the finite buffer is never in overflow. To solve this problem we provide a heuristic algorithm based on Lagrangian optimization using an operational rate-distortion framework and a quantization method follows H.263recommendation.

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Evaluation of Histograms Local Features and Dimensionality Reduction for 3D Face Verification

  • Ammar, Chouchane;Mebarka, Belahcene;Abdelmalik, Ouamane;Salah, Bourennane
    • Journal of Information Processing Systems
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    • v.12 no.3
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    • pp.468-488
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    • 2016
  • The paper proposes a novel framework for 3D face verification using dimensionality reduction based on highly distinctive local features in the presence of illumination and expression variations. The histograms of efficient local descriptors are used to represent distinctively the facial images. For this purpose, different local descriptors are evaluated, Local Binary Patterns (LBP), Three-Patch Local Binary Patterns (TPLBP), Four-Patch Local Binary Patterns (FPLBP), Binarized Statistical Image Features (BSIF) and Local Phase Quantization (LPQ). Furthermore, experiments on the combinations of the four local descriptors at feature level using simply histograms concatenation are provided. The performance of the proposed approach is evaluated with different dimensionality reduction algorithms: Principal Component Analysis (PCA), Orthogonal Locality Preserving Projection (OLPP) and the combined PCA+EFM (Enhanced Fisher linear discriminate Model). Finally, multi-class Support Vector Machine (SVM) is used as a classifier to carry out the verification between imposters and customers. The proposed method has been tested on CASIA-3D face database and the experimental results show that our method achieves a high verification performance.

Implementation of Optical Pattern Recognition System Based on Perceptron Neural Network (Perceptron 신경회로망에 근거한 광 패턴인식 시스템의 구현)

  • 한종욱;용상순;이진호;이기서;김은수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.16 no.6
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    • pp.545-555
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    • 1991
  • In this paper, We discuss optical implementation of new optical adaptive patern recognition system based on single layer perception with learning capability and associative memory model having error corrective capability. The single layer perceptron is optically implemented by using 2 D LCTV spatial light modulators through the nonlinear quantization and polarization encoding methods, and 2 D hopfield associative memory is also implemented by using multifocus holographic lens. From some experimental results on classfication of Arabic numbers into even & edd numbers, it is shown that the proposed system can classify the patterns to the right classes correctly even for the partial and erronenous input patterns. Accordingly, the proposed optical adaptive pattern recognition system can be suggested for practical application in the fields of image processing and pattern recognition.

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Fast Prediction Mode Decision in HEVC Using a Pseudo Rate-Distortion Based on Separated Encoding Structure

  • Seok, Jinwuk;Kim, Younhee;Ki, Myungseok;Kim, Hui Yong;Choi, Jin Soo
    • ETRI Journal
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    • v.38 no.5
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    • pp.807-817
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    • 2016
  • A novel fast algorithm is suggested for a coding unit (CU) mode decision using pseudo rate-distortion based on a separated encoding structure in High Efficiency Video Coding (HEVC). A conventional HEVC encoder requires a large computational time for a CU mode prediction because prediction and transformation procedures are applied to obtain a rate-distortion cost. Hence, for the practical application of HEVC encoding, it is necessary to significantly reduce the computational time of CU mode prediction. As described in this paper, under the proposed separated encoder structure, it is possible to decide the CU prediction mode without a full processing of the prediction and transformation to obtain a rate-distortion cost based on a suitable condition. Furthermore, to construct a suitable condition to improve the encoding speed, we employ a pseudo rate-distortion estimation based on a Hadamard transformation and a simple quantization. The experimental results show that the proposed method achieves a 38.68% reduction in the total encoding time with a similar coding performance to that of the HEVC reference model.

Cyber Character Implementation with Recognition and Synthesis of Speech/lmage (음성/영상의 인식 및 합성 기능을 갖는 가상캐릭터 구현)

  • Choe, Gwang-Pyo;Lee, Du-Seong;Hong, Gwang-Seok
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.37 no.5
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    • pp.54-63
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    • 2000
  • In this paper, we implemented cyber character that can do speech recognition, speech synthesis, Motion tracking and 3D animation. For speech recognition, we used Discrete-HMM algorithm with K-means 128 level vector quantization and MFCC feature vector. For speech synthesis, we used demi-syllables TD-PSOLA algorithm. For PC based Motion tracking, we present Fast Optical Flow like Method. And for animating 3D model, we used vertex interpolation with DirectSD retained mode. Finally, we implemented cyber character integrated above systems, which game calculating by the multiplication table with user and the cyber character always look at user using of Motion tracking system.

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Implementation of A Fast Preprocessor for Isolated Word Recognition (고립단어 인식을 위한 빠른 전처리기의 구현)

  • Ahn, Young-Mok
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.1
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    • pp.96-99
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    • 1997
  • This paper proposes a very fast preprocessor for isolated word recognition. The proposed preprocessor has a small computational cost for extracting candidate words. In the preprocessor, we used a feature sorting algorithm instead of vector quantization to reduce the computational cost. In order to show the effectiveness of our preprocessor, we compared it to a speech recognition system based on semi-continuous hidden Markov Model and a VQ-based preprocessor by computing their recognition performances of a speaker independent isolated word recognition. For the experiments, we used the speech database consisting of 244 words which were uttered by 40 male speakers. The set of speech data uttered by 20 male speakers was used for training, and the other set for testing. As the results, the accuracy of the proposed preprocessor was 99.9% with 90% reduction rate for the speech database.

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Compressed Channel Feedback for Correlated Massive MIMO Systems

  • Sim, Min Soo;Park, Jeonghun;Chae, Chan-Byoung;Heath, Robert W. Jr.
    • Journal of Communications and Networks
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    • v.18 no.1
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    • pp.95-104
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    • 2016
  • Massive multiple-input multiple-output (MIMO) is a promising approach for cellular communication due to its energy efficiency and high achievable data rate. These advantages, however, can be realized only when channel state information (CSI) is available at the transmitter. Since there are many antennas, CSI is too large to feed back without compression. To compress CSI, prior work has applied compressive sensing (CS) techniques and the fact that CSI can be sparsified. The adopted sparsifying bases fail, however, to reflect the spatial correlation and channel conditions or to be feasible in practice. In this paper, we propose a new sparsifying basis that reflects the long-term characteristics of the channel, and needs no change as long as the spatial correlation model does not change. We propose a new reconstruction algorithm for CS, and also suggest dimensionality reduction as a compression method. To feed back compressed CSI in practice, we propose a new codebook for the compressed channel quantization assuming no other-cell interference. Numerical results confirm that the proposed channel feedback mechanisms show better performance in point-to-point (single-user) and point-to-multi-point (multi-user) scenarios.

Design and Applications of a Generalized Software-Based GNSS IF Signal Generator

  • Lim, Deok-Won;Park, Chan-Sik;Lee, Sang-Jeong
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.2
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    • pp.211-215
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    • 2006
  • In this paper, design and applications of a generalized, versatile and customizable IF signal generator that can model the modernized GPS and Galileo signal is given. It generates IF sampled data that can be directly used by a software receiver. Entire constellation of satellites which is independent of satellite-user geometry is easily determined using a real or simulated ephemeris data. Since the IF center frequency, sampling frequency and quantization bit number are user location dependent parameters, their effects are also considered in IF signal generator. The generalized IF signal generator will be very well suited for the development phase of a software receiver due to its versatility. The full access to the sampling frequency, front-end filter definition and ADC parameters also offers a great opportunity for cost-effective analysis of tracking loops and error mitigation techniques at the receiver level. Interference sources can be easily added to the generator to simulate specific environments. This software IF signal generator can also be used to feed a multi-frequency multi-system software receiver for the prototyping of a combined GPS/Galileo receiver. The test result using the generated signals and a real software receiver shows the effectiveness of the implemented IF signal generator.

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Indoor Localization in Wireless Sensor Network using LVQ (LVQ를 이용한 무선 센서 네트워크의 실내 위치 인식)

  • Park, Jin-Woo;Jung, Kyung-Kwon;Eom, Ki-Hwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.5
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    • pp.1295-1302
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    • 2010
  • This paper proposed indoor location recognition method based on RSSI(received signal strength indication) using the LVQ network. In order to verify the effectiveness of the proposed method, we performed experiments, and then compared to the conventional triangularity measurement method. In the experiments, we set up the system to the laboratory, divided the 40 section, and installed 6 nodes as a reference node. We obtained the log-normal path loss model of wireless channels, RSSI converted into the distance. The distance values used as the input of LVQ. To learn the LVQ network, we set the target values as section indices. In the experiments, we determined the optimal number of subclass, and confirmed that the success rate of training phase was 96%, test phase was 91%.

A Statistic Correlation Analysis Algorithm Between Land Surface Temperature and Vegetation Index

  • Kim, Hyung-Moo;Kim, Beob-Kyun;You, Kang-Soo
    • Journal of Information Processing Systems
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    • v.1 no.1 s.1
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    • pp.102-106
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    • 2005
  • As long as the effective contributions of satellite images in the continuous monitoring of the wide area and long range of time period, Landsat TM and Landsat ETM+ satellite images are surveyed. After quantization and classification of the deviations between TM and ETM+ images based on approved thresholds such as gains and biases or offsets, a correlation analysis method for the compared calibration is suggested in this paper. Four time points of raster data for 15 years of the highest group of land surface temperature and the lowest group of vegetation of the Kunsan city Chollabuk_do Korea located beneath the Yellow sea coast, are observed and analyzed their correlations for the change detection of urban land cover. This experiment based on proposed algorithm detected strong and proportional correlation relationship between the highest group of land surface temperature and the lowest group of vegetation index which exceeded R=(+)0.9478, so the proposed Correlation Analysis Model between the highest group of land surface temperature and the lowest group of vegetation index will be able to give proof an effective suitability to the land cover change detection and monitoring.