• International Journal of Contents
• /
• 제10권3호
• /
• pp.17-25
• /
• 2014

In this paper, we describe an adaptive Markov chain Monte Carlo-based particle filter that effectively addresses real-time multi-face tracking on mobile platforms. Because traditional approaches based on a particle filter require an enormous number of particles, the processing time is high. This is a serious issue, especially on low performance devices such as mobile phones. To resolve this problem, we developed a tracker that includes a more sophisticated likelihood model to reduce the number of particles and maintain the identity of the tracked faces. In our proposed tracker, the number of particles is adjusted during the sampling process using an adaptive sampling scheme. The adaptive sampling scheme is designed based on the average acceptance ratio of sampled particles of each face. Moreover, a likelihood model based on color information is combined with corner features to improve the accuracy of the sample measurement. The proposed tracker applied on various videos confirmed a significant decrease in processing time compared to traditional approaches.

• Proceedings of the IEEK Conference
• /
• 대한전자공학회 2001년도 하계종합학술대회 논문집(1)
• /
• pp.89-92
• /
• 2001

In this paper, adaptive multi-stage parallel interference cancellation (PIC) receiver is considered for a multi-rate DS-CDMA system. In each stage of the adaptive multi-stage PIC receiver, multiple access interference (MAI) estimates are obtained using the sub-bit estimates from the Previous stage and the adaptive weights for the sub-bit estimates. The adaptive weights are obtained by minimizing the mean squared error between the received signal and its estimate through a least mean square (LMS) algorithm. It is shown that the adaptive multi- stage PIC receiver achieves smaller BER than the matched filter receiver, multi-stage PIC receiver, and multi-stage partial PIC receiver for the multi-rate DS-CDMA system in a Rayleigh fading channel.

• Journal of Broadcast Engineering
• /
• 제8권2호
• /
• pp.204-208
• /
• 2003

In this paper, a new matrix vector formulation for a wavelet-based subband decomposition is introduced. This formulation provides a means to compute a regular multi-resolution analysis over many levels of decomposition. With this approach. any single channel linear space-invariant filtering problem can be cast into a multi-channel framework. This decomposition Is applied to the linear space-invariant image restoration problem and propose a frequency-adaptive constrained least squares(CLS) filter. In the proposed filter, we use different parameters adaptively according to subband characteristics. Experimental results are presented for the proposed frequency-adaptive CLS filter These experiments show that if accurate estimates of the subband characteristics are available, the proposed frequency adaptive CLS filter provides significant improvements over the traditional single channel filter.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• 제58권11호
• /
• pp.2299-2301
• /
• 2009

The adaptive IIR filters for active noise control systems are more effective when acoustic feedback exists, but the adaptive IIR filters could be unstable when the filter algorithm is not yet converged. In this paper, auto-secondary path estimation techniques and a stabilizing process for adaptive Multi-Channel Recursive LMS (MCRLMS) filters are developed to improve the stability of multi-channel active noise control systems. Experiments using a TMS320VC33 digital signal processor in a three dimensional enclosure have performed to show the effectiveness of the proposed algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• 제29권1호
• /
• pp.139-144
• /
• 2005

A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion. have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• 제38권4호
• /
• pp.77-77
• /
• 2001

MMMF(Modified 2D Multi-shell Median Filter)를 기초로 하여 가변 문턱 조건과 홀/짝수 다중셀을 이용한 Adaptive Odd/Even MMF(Multi-shell Median Filter)를 제안하였다. 제안된 알고리즘은 MATLAB을 이용하여 연구하고 테스트하였다. 제안된 알고리즘의 성능은 이미 잘 알려진 이미지에 임펄스 노이즈(Impulse Noise)와 Line Missing을 적용하여 평가하였고 이를 FPGA로 구현하였다. 제안된 가변 문턱 조건은 연산 시간과 불필요한 재배치를 줄였고, 홀수 셀과 짝수 셀은 각각 십자 방향과 대각선 방향의 Line Missing을 복구하였다. 특히 짧은 연산 시간으로 실시간을 요구하는 이미지 처리 분야에서 효과적으로 이용할 수 있다.

• Progress in Superconductivity
• /
• 제5권1호
• /
• pp.26-30
• /
• 2003

Magneto-cardiogram(MCG) signals may be highly distorted by the environmental noise, such as power-line interference, broadband white noise, surrounding magnetic noise, and baseline wondering. Several kinds of digital filters and noise cancellation methods have been designed and realized by many researchers, but these methods gave some problems that the original signal may be distorted by digital filter due to the wideband characteristics of background noise. To eliminate noise effectively without distortion of MCG signals, we performed multi-level frequency decomposition using wavelet packets and local adaptive noise cancellation in each local frequency range. In addition to the proposed wavelet filter to eliminate these various non-stationary noise elements, the local adaptive filter using the least mean square(LMS) algorithm and the soft threshold do-noising method are introduced in this paper. The signal to noise ratio(SNR) and the reconstruction square error(RSE) are calculated to evaluate the performance of the proposed method and compared with the results of the conventional wavelet filter and adaptive filter. The experimental results show that the proposed local adaptive filtering method is better than the conventional methods.

• Journal of Broadcast Engineering
• /
• 제17권6호
• /
• pp.1048-1060
• /
• 2012

In this paper, an adaptive temporal and spatial filter (ATSF) based on mean square error (MSE) estimation is proposed. ATSF is a block based de-noising algorithm. Each noisy block is selectively filtered by a temporal filter or a spatial filter. Multi-hypothesis motion compensated filter (MHMCF) and bilateral filter are chosen as the temporal filter and the spatial filter, respectively. Although there is no original video, we mathematically derivate a formular to estimate the real MSE between a block de-noised by MHMCF and its original block and a linear model is proposed to estimate the real MSE between a block de-noised by bilateral filter and its original block. Finally, each noisy block is processed by the filter with a smaller estimated MSE. Simulation results show that our proposed algorithm achieves substantial improvements in terms of both visual quality and PSNR as compared with the conventional de-noising algorithms.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 한국공작기계학회 2004년도 추계학술대회 논문집
• /
• pp.345-351
• /
• 2004

This Paper describes a nonlinear adaptive noise filter using neural network for digital controller system. Back-Propagation Learning Algorithm based MLP (Multi Layer Perceptron)is used an adaptive filters. In this paper. it assume that the noise of primary input in the adaptive noise canceller is not the same characteristic as that of the reference input. Experimental reaults show that the neural network base noise canceller outperforms the linear noise canceller. Especially to make noise cancel close to realtime, Primary input is divided by unit and each divided part is processed for very short time than all the processed data are unified to whole data.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
• /
• pp.349-354
• /
• 2006

For robust INS/GPS navigation system, an efficient multi-filter fusion technique is proposed. In the filtering for nonlinear systems, the representative filter - EKF, and the alternative filters - RHKF filter, SPKF, etc. have individual advantages and weak points. The key concept of the multi-filter fusion is the mergence of the strong points of the filters. This paper fuses the IIR type filter - EKF and the FIR type filter - RHKF filter using the adaptive strategy. The result of the fusion has several advantages over the EKF, and the RHKF filter. The advantages include the robustness to the system uncertainty, temporary unknown bias, and so on. The multi-filter fusion technique is applied to the tightly coupled INS/GPS navigation system and the performance is verified by simulation.