Earticle

In this paper, a prediction system is proposed to control the brightness of smart street lamps by predicting the moving path through the reduction of consumption power and information of pedestrian’s past moving direction while meeting the function of existing smart street lamps. The brightness of smart street lamps is adjusted by utilizing the walk tracking vector and soft hand-off characteristics obtained through the motion sensing sensor of smart street lamps. In addition, the motion vector is used to analyze and predict the pedestrian path, and the GPU is used for high-speed computation. Pedestrians were detected using adaptive Gaussian mixing, weighted difference imaging, and motion vectors, and motions of pedestrians were analyzed using the extracted motion vectors. The preprocessing process using linear interpolation is performed to improve the performance of the proposed prediction system. Fuzzy prediction system and neural network prediction system are designed in parallel to improve efficiency and rough set is used for error correction.

As more computer game integrates with video and working under mobile environments, it requires seamless bandwidth limited video transport environment including integrated game video compression and real time video conference between game users. Video transmission system consists of encoder and decoder. In communication environment, when the encoder transmits the stream data to the decoder, the bit-stream is alternated or lost because of various channel noises. Altered and lost bit-stream data cause the loss of the video data intensity value or motion vector (MV) value. These lost data cause serious damage of the video quality. In this paper, we propose MV recovery method because MV is essential information to keep the better video quality. To recover the lost MV, we use adjacent block’s MV as input data of Kalman filter to estimate the optimized value for current block’s lost MV. In our experimentation with the standard video image: Mobile&Calendar and Susie, our proposed method achieved 0.497dB ~ 1.898dB improvements on video quality over no MV recovery and achieved average 0.03dB ~ 0.725dB improvements over SRMC scheme.

The passengers suffer much inconvenience in a crowded subway during rush hour. The hybrid passenger density estimation (PDE) or information (PDI) system is proposed for maximizing the metro-users' convenience and saving their elapsed time to the destination. The hybrid PDIS technology is comprised of image processing for extracting passengers' head colors/motion vectors and RFID/NFC sensing for measuring the number of passengers. As a result, we can estimate fully the state of passenger density. As the system and its administrator reflect the appr

In this paper, we present a practical identification approach of video fragment for digital video files. Before analyzing the video content, we must decode it based on its encoding format first. In order to effectively identify the format of a fragment, a format classification is performed before the format identification. The methods of format classification and identification are discriminative subspace clustering (DiSC) and the K-nearest neighbor (KNN).Because of losing the meta-information, we add a maximum similar header (MSH) to the front of the fragment to recover the video content. We adopt a simple key frame detection method using standard deviation and mean value. Motion vectors of macro blocks are utilized to classify the video features for effectively identifying the video. Several edges of frames are accumulated and compose a video feature. The experimental results show the evaluations of the video format classification and identification, fragment recovery, and content identification.

In Video coding, Motion Estimation(ME) is the major step to remove the temporal redundancy between adjacent frames. Several algorithms have been developed for acceleration of ME by reducing the number of computations. In this paper, we propose, two- step motion estimation technique to minimize the computational overhead of general full search block matching motion estimation algorithm. In our proposed methodology, we first find the matching block using the trace and upon match, the Sum of Absolute Difference (SAD) is calculated for the entire block in order to ensure the best match motion prediction. In trace matching, the number of computations observed are O(n) rather than O(n2)in case of full search. Hence, the two- step methodology reduces the computational overhead and also ensures compression quality comparable with the existing fast motion search techniques.

본 논문은 광마우스의 패턴 잡음에 대한 움직임 벡터 값에 대해서 디지털 필터링을 통하여 특성 개선 내용을 기술한다. 설계된 회로는 PS2나 USB로 출력되기 전에 x축과 y축 움직임 벡터에 대해 필터링과 평균값을 취하여, 광 마우스의 이동을 부드럽게 하고 떨림 현상을 개선하였다. FPGA를 이용해서 각각의 기능을 검증하고 0.35㎛ 표준 CMOS 공정을 이용하여 칩으로 제작해서 성능을 측정하였다. 시스템 클럭 주파수는 6㎒를 사용하여 1/1700sec 마다 +6에서 -6사이의 움직임 벡터 값을 출력한다. 테스트는 카테시안 로봇을 이용하여 특성에 대한 측정을 실시하였다.

In this paper, we describe the contents of noise characteristic enhancement using digital filtering to the motion vector in the pattern noise of optical mouse. The designed circuit is implemented to enhance the smoothing and trembling with filtering and averaging of x, y motion vector before PS2 or USB output. The function is verified by using FPGA and the performance is measured by the fabricated chip using 0.35㎛ standard CMOS process. The system clock is 6㎒ and the motion vector has the range of +6 to -6 per 1/1700sec. It is tested using the Cartesian robot to measure the noise characteristic enhancement.

This paper proposes a new fragile video watermarking algorithm based on motion vector, we first use the frame difference method to detect moving targets, determine the motion macro blocks. Then in the macroblock by the diamond search, the fragile watermark is embedded in the P-frame motion vectors for inter prediction, so that by changing the mapping of pixel precision motion vector is to be embedded watermark information embedding watermark information. Experimental results show little effect on the video quality of the algorithm.

본 논문에서는 광센서에서 화면상의 픽셀에 대한 변형된 움직임 벡터 추출 알고리즘을 제안한다. 기존 블록 매칭 알고리즘보다 움직임 추출의 정확성을 높이고 연산량을 줄이도록 설계하였다. 제안된 알고리즘은 Cyclone과 삼성 0.35um CMOS 1-poly-4-metal 공정을 이용하여 칩으로 제작하였다. CARTESIAN ROBOT을 이용하여 제작된 칩의 테스트 결과 원하는 성능을 만족하였다.

In this paper, we propose modified algorithm of motion vector detection for the pixel of image in the optical sensor. It is designed to reduce the amount of operation and have more accuracy in the motion detection than previous block matching algorithm. The proposed algorithm is implemented with Cyclone and fabricated using SEC 0.35um CMOS 1-poly-4-metal technology. The result of test with CARTESIAN ROBOT meets the desired performance.

디지털 TV의 동영상 표준인 MPEG2는 방대한 양의 디지털 데이터를 발생한다. 그러나 현재 사용하고 있는 디지털 저장 매체의 수용 능력에는 한계가 있으므로 저장을 위해 전송된 high bit rate의 MPEG2 bitstream을 더욱 낮은 bit rate의 bitstream으로 전환하는 transcoding 기법이 반드시 필요하다. 기존의 encoder와 decoder를 이용하여 구현 가능한 장점이 있는 cascade transcoder는 reencoding시 motion estimation에 많은 수행 시간이 소요되므로, motion estimation 과정을 최소화하면서 optimal motion vector를 구할 수 있는 motion vector refinement 기법을 MPEG2 cascade transcoder에 적용하였다. 결과 처리 속도는 3-5배 향상되었고 화질은 기존의 72 transcoder에 비해 평균 0.1dB 이상의 FSNR 향상이 있었다. 또한 1Mbps와 같은 low bit rate에서 더욱 큰 화질 향상이 있었다.

We propose a motion-compensated frame interpolation method in which an accurate backward/forward motion vector pair (MVP) is estimated based on a parabolic motion model. A reliability measure for an MVP is also proposed to select the most reliable MVP for each interpolated block. The possibility of deformation of bidirectional corresponding blocks is estimated from the selected MVP. Then, each interpolated block is produced by combining corresponding blocks with the weights based on the possibility of deformation. Experimental results show that the proposed method improves PSNR performance by up to 2.8 dB as compared to conventional methods and achieves higher visual quality without annoying blockiness artifacts.

본 논문은 영상의 움직임 특성을 참조하여 움직임 벡터 수평-수직 성분중 하나를 최적의 예측 움직임 벡터 성분으로 선택하여 사용할 수 있는 개선된 교차 움직임벡터 부호화 방법을 제시한다. 제안방법은 부-복호화를 수행할 움직임 벡터 성분의 순서를 복호화기에 알리는 신호비트를 별도로 보낼 필요 없이, 시공간적 움직임필드의 특성을 참조하여 적절한 움직임벡터 성분 예측치를 적응적으로 사용할 수 있다. 기존 H.264/AVC 방법과 비교한 실험 결과, 평균적으로 전체 비트량을 약 1.99% (최대 8.71%) 감소시킬 수 있음을 보여준다.

This paper proposes an improved design of an interleaved motion vector coding scheme with flexibility in predictive motion vector component by exploiting motion characteristics. It can use component-wise adaptive motion vector predictor based on the utility of spatial and temporal motion field without any signaling bit for indicating decoder of the selected predictive motion vector component. Experiment with test video data shows about 1.99% (max 8.71%) bit rate reduction compared to the conventional H.264/AVC method.

In H.264, sub-pel motion estimation (ME) has strong effect when coding video sequences. 1/4-pel performs better at low bitrate while 1/8-pel gives better results at high bitrate. In this paper, a variable sub-pixel motion vector resolution based on block mode motion estimation method is proposed. Experiment results show that the proposed method can take the advantage of 1/4-pel at low bitrate and 1/8-pel at high bitrate. In addition to that, time is reduced from 14% to 53% compared to KTA1.3 with 1/8-pel motion vector (MV) resolution.

Various Motion Estimation (ME) algorithms have been proposed since ME requires large computational complexity. The proposed algorithm employs Enhanced Cross Search Pattern (ECSP) using motion vector of neighbor-blocks to search the motion vector. The experimental results show that proposed algorithm reduces the search point up to 35% compared to conventional methods.

In error-prone wireless environments, it is difficult to realize video coding systems that are robust to various types of data loss. In this paper, a novel motion-vector refinement approach is presented for video error concealment. A traditional boundary-matching approach is exploited to reduce blocky effects along the block boundary. More specifically, a downhill simplex approach is combined with a boundary-matching approach to fine-tune the motion vectors, reducing the blocky effects along the prediction unit block boundary, and minimizing the computational cost. Extensive simulations are performed, and the results obtained verify the robustness and effectiveness of the proposed approach.

This paper presents a new algorithm that includes a mechanism to avoid local solutions in a motion vector detection method that uses the steepest descent method. Two different implementations of the algorithm are demonstrated using two major search methods for tree structures, depth first search and breadth first search. Furthermore, it is shown that by avoiding local solutions, both of these implementations are able to obtain smaller prediction errors compared to conventional motion vector detection methods using the steepest descent method, and are able to perform motion vector detection within an arbitrary upper limit on the number of computations. The effects that differences in the search order have on the effectiveness of avoiding local solutions are also presented.

In this paper, an adaptive motion vector smoothing scheme based on weighted vector median filtering is proposed in order to eliminate the motion outliers more effectively for improving the quality of side information in frame-based distributed video coding. We use a simple motion vector outlier reliability measure for each block in a motion compensated interpolated frame and apply weighted vector median filtering only to the blocks with unreliable motion vectors. Simulation results show that the proposed adaptive motion vector smoothing algorithm improves the quality of the side information significantly while maintaining low complexity at the encoder in frame-based distributed video coding.

기존의 탐색 알고리즘은 탐색 창 내의 원점에서 탐색을 시작한다. 하지만 영상은 일정한 방향으로 규칙적으로 움직이는 것이 많기 때문에 Frame$_t$ 의 움직임 벡터(MV)가 Frame$_{t-1}$의 움직임 벡터와 같을 가능성이 크다. 이를 참고하여 본 논문에서는 시작점을 원점뿐만 아니라 Frame$_{t-1}$의 MV까지도 예측 시작점으로 선택하여 탐색의 시작점을 다양화 하였다. 실험 결과 탐색 시작점을 다양화 함으로써 full search를 제외한 diamond search, hexagonal search, 4 step search등 기존의 탐색 알고리즘보다 30$\sim$80% 더 작은 SAD값을 구할 수 있었다.

사용자에게 편리한 인터페이스를 제공하는 IT 기기가 널리 보급되면서 직관적인 인터페이스 기술에 대한 관심이 높아지고 있다. 이미지 센서로 입력된 사람의 손 모양이나 움직임을 이용하는 인터페이스가 그 중 하나이다. 한 편 이미지 센서 영상을 저장하기 위하여 H.264/AVC와 같은 영상 압축 기술이 사용된다. 영상을 압축하기 위해 부호기는 모든 Macroblock에서 움직임 추정을 수행한다. 추정된 움직임 정보는 손 움직임을 인식하는데 사용될 수 있고 이를 통해 전자 기기에 명령을 내리는 인터페이스 기술의 한 부분을 구현하는 것이 가능하다. 본 논문은 H.264/AVC 부호기의 Motion Vector를 이용하는 손 추적 알고리즘을 제시한다. 제시된 알고리즘은 손 움직임 추적의 정확도를 향상시키기 위하여 Motion Vector보다 신뢰도가 높은 Motion Density Map 정보를 사용한다. 이 정보를 이용하여 이동한 손을 포함하는 손 윈도우를 결정한다. 실험 결과를 통하여 제시된 알고리즘이 손의 움직임을 추적하는 것을 확인할 수 있다.

In this paper we propose a new deinterlacing method with block classification and motion vector smoothing. The proposed method classifies a block, then depending on the region it belongs to, the motion estimation or line averaging is applied. To classify a block its variance is calculated. Then, for those blocks that belong to simple non-texture region the line averaging is done while motion estimation is applied to complex region. The motion vector field is smoothed using median filter what yields more accurate interpolation. In the experiments for the subjective evaluation, the proposed method bas shown satisfying results in terms of computation time consumption and peak signal-to-noise ratio. Due to the simplicity of the algorithm computation time was drastically decreased.