• Title/Summary/Keyword: 동작벡터

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HMM-based Intent Recognition System using 3D Image Reconstruction Data (3차원 영상복원 데이터를 이용한 HMM 기반 의도인식 시스템)

  • Ko, Kwang-Enu;Park, Seung-Min;Kim, Jun-Yeup;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.2
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    • pp.135-140
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    • 2012
  • The mirror neuron system in the cerebrum, which are handled by visual information-based imitative learning. When we observe the observer's range of mirror neuron system, we can assume intention of performance through progress of neural activation as specific range, in include of partially hidden range. It is goal of our paper that imitative learning is applied to 3D vision-based intelligent system. We have experiment as stereo camera-based restoration about acquired 3D image our previous research Using Optical flow, unscented Kalman filter. At this point, 3D input image is sequential continuous image as including of partially hidden range. We used Hidden Markov Model to perform the intention recognition about performance as result of restoration-based hidden range. The dynamic inference function about sequential input data have compatible properties such as hand gesture recognition include of hidden range. In this paper, for proposed intention recognition, we already had a simulation about object outline and feature extraction in the previous research, we generated temporal continuous feature vector about feature extraction and when we apply to Hidden Markov Model, make a result of simulation about hand gesture classification according to intention pattern. We got the result of hand gesture classification as value of posterior probability, and proved the accuracy outstandingness through the result.

Performance Evaluation of a Peak Windowing-Based PAPR Reduction Scheme in OFDM Polar Transmitters (OFDM polar transmitter에서 피크 윈도잉 기반의 PAPR 감소기법의 성능평가)

  • Seo, Man-Jung;Shin, Hee-Sung;Im, Sung-Bin;Jung, Jae-Ho;Lee, Kwang-Chun
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.45 no.12
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    • pp.42-48
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    • 2008
  • Next generation wireless communication systems require RF transceivers that enable multiband/multimode operations. Polar transmitters are known as good candidates for high data rate systems such as EDGE (Enhanced Data Rates for GSM Evolution), WCDMA (Wideband Code Division Multiple Access), and WLAN (Wireless Local Area Network) because they can obtain high efficiency by using efficient switched-mode RF power amplifiers. In this paper, we investigate the performance of a simple peak windowing scheme for the OFDM (Orthogonal frequency Division Multiplexing) polar transmitter, which requires no change of a receiver structure or no additional information transmission. The approach we employed is to apply the peak windowing scheme to the amplitude modulated signals of the polar transmitter to reduce the PAPR (Peak-to-Average Power Ratio). The BER (Bit Error Rate) and EVM (Error Vector Magnitude) performances are measured for various window types and lengths. The simulation results demonstrate that the proposed algorithm mitigates out-of-band distortion introduced by clipping along with PAPR reduction.

Speaker-Independent Korean Digit Recognition Using HCNN with Weighted Distance Measure (가중 거리 개념이 도입된 HCNN을 이용한 화자 독립 숫자음 인식에 관한 연구)

  • 김도석;이수영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.10
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    • pp.1422-1432
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    • 1993
  • Nonlinear mapping function of the HCNN( Hidden Control Neural Network ) can change over time to model the temporal variability of a speech signal by combining the nonlinear prediction of conventional neural networks with the segmentation capability of HMM. We have two things in this paper. first, we showed that the performance of the HCNN is better than that of HMM. Second, the HCNN with its prediction error measure given by weighted distance is proposed to use suitable distance measure for the HCNN, and then we showed that the superiority of the proposed system for speaker-independent speech recognition tasks. Weighted distance considers the differences between the variances of each component of the feature vector extraced from the speech data. Speaker-independent Korean digit recognition experiment showed that the recognition rate of 95%was obtained for the HCNN with Euclidean distance. This result is 1.28% higher than HMM, and shows that the HCNN which models the dynamical system is superior to HMM which is based on the statistical restrictions. And we obtained 97.35% for the HCNN with weighted distance, which is 2.35% better than the HCNN with Euclidean distance. The reason why the HCNN with weighted distance shows better performance is as follows : it reduces the variations of the recognition error rate over different speakers by increasing the recognition rate for the speakers who have many misclassified utterances. So we can conclude that the HCNN with weighted distance is more suit-able for speaker-independent speech recognition tasks.

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Development of Recognition Application of Facial Expression for Laughter Theraphy on Smartphone (스마트폰에서 웃음 치료를 위한 표정인식 애플리케이션 개발)

  • Kang, Sun-Kyung;Li, Yu-Jie;Song, Won-Chang;Kim, Young-Un;Jung, Sung-Tae
    • Journal of Korea Multimedia Society
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    • v.14 no.4
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    • pp.494-503
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    • 2011
  • In this paper, we propose a recognition application of facial expression for laughter theraphy on smartphone. It detects face region by using AdaBoost face detection algorithm from the front camera image of a smartphone. After detecting the face image, it detects the lip region from the detected face image. From the next frame, it doesn't detect the face image but tracks the lip region which were detected in the previous frame by using the three step block matching algorithm. The size of the detected lip image varies according to the distance between camera and user. So, it scales the detected lip image with a fixed size. After that, it minimizes the effect of illumination variation by applying the bilateral symmetry and histogram matching illumination normalization. After that, it computes lip eigen vector by using PCA(Principal Component Analysis) and recognizes laughter expression by using a multilayer perceptron artificial network. The experiment results show that the proposed method could deal with 16.7 frame/s and the proposed illumination normalization method could reduce the variations of illumination better than the existing methods for better recognition performance.

The Motion Estimator Implementation with Efficient Structure for Full Search Algorithm of Variable Block Size (다양한 블록 크기의 전역 탐색 알고리즘을 위한 효율적인 구조를 갖는 움직임 추정기 설계)

  • Hwang, Jong-Hee;Choe, Yoon-Sik
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.46 no.11
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    • pp.66-76
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    • 2009
  • The motion estimation in video encoding system occupies the biggest part. So, we require the motion estimator with efficient structure for real-time operation. And for motion estimator's implementation, it is desired to design hardware module of an exclusive use that perform the encoding process at high speed. This paper proposes motion estimation detection block(MED), 41 SADs(Sum of Absolute Difference) calculation block, minimum SAD calculation and motion vector generation block based on parallel processing. The parallel processing can reduce effectively the amount of the operation. The minimum SAD calculation and MED block uses the pre-computation technique for reducing switching activity of the input signal. It results in high-speed operation. The MED and 41 SADs calculation blocks are composed of adder tree which causes the problem of critical path. So, the structure of adder tree has changed the most commonly used ripple carry adder(RCA) with carry skip adder(CSA). It enables adder tree to operate at high speed. In addition, as we enabled to easily control key variables such as control signal of search range from the outside, the efficiency of hardware structure increased. Simulation and FPGA verification results show that the delay of MED block generating the critical path at the motion estimator is reduced about 19.89% than the conventional strukcture.