• Title/Summary/Keyword: fast search

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Fast Codebook Search Algorithm for VQ of Subband Images (서브밴드 영상의 VQ를 위한 고속 코드북 탐색 알고리즘)

  • Hwang, Jae-Ho;Hong, Choong-Seon;Lee, Dae-Young
    • Annual Conference of KIPS
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    • 2000.10b
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    • pp.883-886
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    • 2000
  • Two fast search algorithms are proposed for VQ encoding in subband/VQ coding schemes. These algorithms exploit the property of the transform domain that the large coefficients rarely exist in the decomposed subbands. And the exit condition of PDE algorithm can be satisfied by comparing the large values of the codeword with the corresponding ones of the input vector. The computational complexity can be reduced at the expense of memories without extra coding errors.

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Fast Ambiguity Determination Method(FADM) for Carrier Phase GPS and Performance Analysis (반송파위성 GPS를 위한 빠른 미지정수 결정 기법 및 성능 분석)

  • Park, Gyu-Il;Oh, Min-Seok;Shim, Duk-Sun
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.12
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    • pp.1036-1043
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    • 2001
  • It is well-known that positioning accuracy can be improved by the use of carrier phase of GPS up to the centimeter level. In order to obtain good accuracy, we need to know integer ambiguity in the carrier phase accurately. In this paper, we propose a fast ambiguity determination method(FADM) which combines Kalman filtering and the search method, and show the improvement of the positioning performance by static and kinematic simulation compared with known methods such as Kalman filtering, LSAST (Least Squares Ambiguity Search Technique), ARCE(Ambiguity Resolution with Constratint Equation), LLL(Lenstra, Lenstra, and Lovasz) algorithms.

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Real-Time Tracking for Moving Object using Neural Networks (신경망을 이용한 이동성 칼라 물체의 실시간 추적)

  • Choi, Dong-Sun;Lee, Min-Jung;Choi, Young-Kiu
    • Proceedings of the KIEE Conference
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    • 2001.07d
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    • pp.2358-2361
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    • 2001
  • In recent years there have been increasing interests in real-time object tracking with image information. Since image information is affected by illumination, this paper presents the real-time object tracking method based on neural networks which have robust characteristics under various illuminations. This paper proposes three steps to track the object and the fast tracking method. In the first step the object color is extracted using neural networks. In the second step we detect the object feature information based on invariant moment. Finally the object is tracked through a shape recognition using neural networks. To achieve the fast tracking performance, this paper first has a global search of entire image and tracks the object through local search when the object is recognized.

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A Study on the New BC-ABBM Motion Estimation Algorithm for Low Bit Rate Video Coding (저 전송률 비디오 압축을 위한 새로운 BC-ABBM 움직임 추정 알고리즘에 관한 연구)

  • 이완범;김환용
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.7C
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    • pp.946-953
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    • 2004
  • Fast search and conventional boolean matching motion estimation algorithms reduce computational complexity and data processing time but this algorithms have disadvantages that is difficult of implementation of hardware because of high control overhead and that is less performance than Full search Algorithm(FA). This paper present new all binary block matching algorithm, called Bit Converted All Binary Block Matching(BC-ABBM). Proposed algorithm have performance closed to the FA by boolean only block matching that may be very efficiently implemented in hardware for low bit rate video communication. Simulation results show that the PSNR of the proposed algorithm is about 0.04dB loss than FA but is about 0.6 ∼ 1.4dB gain than fast search algorithm and conventional boolean matching algorithm.

A Fast Intra Skip Detection Algorithm for H.264/AVC Video Encoding

  • Kim, Byung-Gyu;Kim, Jong-Ho;Cho, Chang-Sik
    • ETRI Journal
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    • v.28 no.6
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    • pp.721-731
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    • 2006
  • A fast intra skip detection algorithm based on the ratedistortion (RD) cost for an inter frame (P-slices) is proposed for H.264/AVC video encoding. In the H.264/AVC coding standard, a robust rate-distortion optimization technique is used to select the best coding mode and reference frame for each macroblock (MB). There are three types of intra predictions according to profiles. These are $16{\times}16$ and $4{\times}4$ intra predictions for luminance and an $8{\times}8$ intra prediction for chroma. For the high profile, an $8{\times}8$ intra prediction has been added for luminance. The $4{\times}4$ prediction mode has 9 prediction directions with 4 directions for $16{\times}16$ and $8{\times}8$ luma, and $8{\times}8$ chrominance. In addition to the inter mode search procedure, an intra mode search causes a significant increase in the complexity and computational load for an inter frame. To reduce the computational load of the intra mode search at the inter frame, the RD costs of the neighborhood MBs for the current MB are used and we propose an adaptive thresholding scheme for the intra skip extraction. We verified the performance of the proposed scheme through comparative analysis of experimental results using joint model reference software. The overall encoding time was reduced up to 32% for the IPPP sequence type and 35% for the IBBPBBP sequence type.

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Fast Variable-size Block Matching Algorithm for Motion Estimation Based on Bit-pattern (비트패턴을 기반으로 한 고속의 적응적 가변 블록 움직임 예측 알고리즘)

  • 신동식;안재형
    • Journal of Korea Multimedia Society
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    • v.3 no.4
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    • pp.372-379
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    • 2000
  • In this paper, we propose a fast variable-size block matching algorithm for motion estimation based on bit-pattern. Motion estimation in the proposed algorithm is performed after the representation of image sequence is transformed 8bit pixel values into 1bit ones depending on the mean value of search block, which brings a short searching time by reducing the computational complexity. Moreover, adaptive searching methods according to the motion information of the block make the procedure of motion estimation efficient by eliminating an unnecessary searching of low motion block and deepening a searching procedure in high motion block. Experimental results show that the proposed algorithm provides better performance-0.5dB PSNR improvement-than full search block matching algorithm with a fixed block size.

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Fast Device Discovery for Remote Device Management in Lighting Control Networks

  • Choi, Sang-Il;Lee, Sanghun;Koh, Seok-Joo;Lim, Sang-Kyu;Kim, Insu;Kang, Tae-Gyu
    • Journal of Information Processing Systems
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    • v.11 no.1
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    • pp.125-133
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    • 2015
  • The Remote Device Management (RDM) protocol is used to manage the devices in the lighting control networks. RDM provides bi-directional communications between a controller and many lighting devices over the DMX512-A network. In RDM, using a simple binary search scheme, which is based on the 48-bit unique ID (UID) of each device, discovers the lighting devices. However, the existing binary search scheme tends to require a large delay in the device discovery process. In this paper, we propose a novel partition-based discovery scheme for fast device discovery in RDM. In the proposed scheme, all devices are divided into several partitions as per the device UID, and the controller performs device discovery for each partition by configuring a response timer that each device will use. From numerical simulations, we can see that there is an optimal number of partitions to minimize the device discovery time for a given number of devices in the proposed scheme, and also that the proposed partition-based scheme can reduce the device discovery time, as compared to the existing binary search scheme.

Fast Integer-Pel Motion Estimation Based on Statistical Property for H.264/AVC (H.264/AVC를 위한 통계 특성 기반 정수 화소 단위 고속 움직임 예측 기법)

  • Noh, Jin-Young;Hong, Min-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.8A
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    • pp.669-678
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    • 2012
  • In this paper, we propose an efficient fast integer-pel motion estimation for H.264/AVC using local statistics of local motion vectors. Using neighboring motion vectors, we define a new statistical property that is used to determine a mode of motion search range of current block. In addition, an adaptive motion search range compensated method that is based on cumulative statistics of previous coded blocks is addressed to solve the problem of the statistical motion search range decision method. Experimental results show that proposed algorithm has the capability to reduce the computational cost over the other methods.

Fast Codevector Search on Vector Quantization (백터양자화기의 신속코더백터 찾기)

  • 우홍체
    • Journal of Korea Society of Industrial Information Systems
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    • v.5 no.2
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    • pp.16-21
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    • 2000
  • Vector quantization(VQ) is widely used in many high-quality and high-rate data compression applications such as speech coding, audio coding, image coding and video coding. When the size of a VQ codebook is large, the computational complexity for the full codeword search method is a significant problem for many applications. A number of complexity reduction algorithms have been proposed and investigated using such properties of the codebook as the triangle inequality. This paper proposes a new fast VQ search algorithm that is based on a multi-stage structure for searching for the best codeword. Even using only two stages, a significant complexity reduction can be obtained without any loss of quality.

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Real-Time Face Detection by Estimating the Eye Region Using Neural Network (신경망 기반 눈 영역 추정에 의한 실시간 얼굴 검출 기법)

  • 김주섭;김재희
    • Proceedings of the IEEK Conference
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    • 2001.06d
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    • pp.21-24
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    • 2001
  • In this paper, we present a fast face detection algorithm by estimating the eye region using neural network. To implement a real time face detection system, it is necessary to reduce search space. We limit the search space just to a few pairs of eye candidates. For the selection of them, we first isolate possible eye regions in the fast and robust way by modified histogram equalization. The eye candidates are paired to form an eye pair and each of the eye pair is estimated how close it is to a true eye pair in two aspects : One is how similar the two eye candidates are in shape and the other is how close each of them is to a true eye image A multi-layer perceptron neural network is used to find the eye candidate region's closeness to the true eye image. Just a few best candidates are then verified by eigenfaces. The experimental results show that this approach is fast and reliable. We achieved 94% detection rate with average 0.1 sec Processing time in Pentium III PC in the experiment on 424 gray scale images from MIT, Yale, and Yonsei databases.

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