The Experts below are selected from a list of 60012 Experts worldwide ranked by ideXlab platform
Wenpeng Ding - One of the best experts on this subject based on the ideXlab platform.
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A fast sub-pixel Motion Estimation algorithm for HEVC
2016 IEEE International Symposium on Circuits and Systems (ISCAS), 2016Co-Authors: Wenpeng DingAbstract:Many fast integer-pixel Motion Estimation algorithms have been developed for the High Efficiency Video Coding Standard, however the speed of sub-pixel Motion Estimation still has room for improvement. A fast sub-pixel Motion Estimation algorithm is proposed in this paper to speed up the sub-pixel search process. First, the proposed scheme skips sub-pixel search process in smooth prediction units. Then a fast sub-pixel search algorithm based on texture direction analysis is proposed to further reduce the computational complexity of subpixel Motion Estimation. The simulation results show that compared with the Full Sub-pixel Search (FSPS), the encoding complexity of the whole Motion Estimation process can be reduced by an average of 40.9% with negligible coding performance loss.
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Multi-stage Hash Based Motion Estimation for HEVC
2015 Data Compression Conference, 2015Co-Authors: Wenpeng Ding, Jizheng XuAbstract:Motion Estimation plays an important role in video coding standards, such as H.264/AVC and HEVC. In this paper, we propose a multi-stage hash based Motion Estimation algorithm for HEVC, which enables hash based Motion Estimation for natural videos. In the proposed method, the prediction blocks significantly different from the current prediction unit will be eliminated in the Motion Estimation process. Locality sensitive hashing functions are used to measure the difference between the input block and predicted blocks. The proposed algorithm is implemented into the HM 12.0 software, and the simulation results show that the complexity of Motion Estimation is significantly reduced with negligible coding performance loss.
Sethuraman Panchanathan - One of the best experts on this subject based on the ideXlab platform.
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Motion Estimation architecture for MPEG-4
Parallel and Distributed Methods for Image Processing III, 1999Co-Authors: Lakshmanan Chandrasekhar, Sethuraman PanchanathanAbstract:Visual Computing and Communications is becoming increasingly important with the advent of broadband networks and compression standards. The International Standards Organization is currently finalizing the MPEG-4 standard, which emphasizes object based coding and content manipulation in video sequences. There are essentially two kinds of redundancies in a video sequence, namely spatial and temporal. The concept of video object planes (VOPs) has been introduced in MPEG-4, which allows for manipulation and coding of the various video objects. The temporal correlation in the VOPs is exploited by employing Motion Estimation/compensation process similar to the MPEG-1 and MPEG-2 standards. However, there are some enhancements to that of the MPEG-4 Motion Estimation procedure particularly in terms of the padding. Motion Estimation process is applied to block sizes for both 8 X 8 and 16 X 16 pixels for the luminance component. In this paper, we propose design of flexible architectures for implementing scalable Motion Estimation and padding. The proposed architecture is modular and has a regular data flow and therefore can be implemented in VLSI.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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Multiresolution Motion Estimation techniques for video compression
Optical Engineering, 1996Co-Authors: M.k. Mandal, E. Chan, Xin Wang, Sethuraman PanchanathanAbstract:The wavelet transform is a valuable tool in video processing because of its flexibility in representing nonstationary signals. Wavelet-based compression has the advantages of efficient decorrelation of image frames and reduced-complexity multiresolution Motion Estimation (MRME). We propose three techniques to improve Motion Estimation in a wavelet-based coder. First, we propose to use an adaptive threshold for coding the Motion vectors of the high-pass subimages. Secondly, we propose a bidirectional Motion Estimation (BMRME) technique in the wavelet transform domain. In BMRME, we estimate the temporal (i.e., direction information) flags only for the blocks in the lowest-resolution subimages and use the same information for the corresponding blocks in the higher-resolution subimages. Finally, we propose a fast multiresolution Motion Estimation technique where the directional subimages at each level of the wavelet pyramid are combined into a single subimage. Multiresolution Motion Estimation is then performed on the newly formed subimages. The proposed techniques improve the coding performance significantly over the baseline MRME technique. In addition, they further reduce the computational complexity of the MRME technique.
Sarp Erturk - One of the best experts on this subject based on the ideXlab platform.
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two bit transform for binary block Motion Estimation
IEEE Transactions on Circuits and Systems for Video Technology, 2005Co-Authors: Alp Erturk, Sarp ErturkAbstract:One-bit transforms (1BTs) have been proposed for low-complexity block-based Motion Estimation by reducing the representation order to a single bit, and employing binary matching criteria. However, as a single bit is used in the representation of image frames, bad Motion vectors are likely to be resolved in 1BT-based Motion Estimation algorithms particularly for small block sizes. It is proposed in this paper to utilize a two-bit transform (2BT) for block-based Motion Estimation. Image frames are converted into two-bit representations by a simple block-by-block two bit transform based on multithresholding with mean and linearly approximated standard deviation values. In order to avoid blocking effects at block boundaries during the block-by-block transformation while enabling the two-bit representation to be constructed according to local detail, threshold values are computed within a larger window surrounding the transforming block. The 2BT makes use of lower bit-depth and binary matching criteria properties of 1BTs to achieve low-complexity block Motion Estimation. The 2BT improves Motion Estimation accuracy and seriously reduces the amount of bad Motion vectors compared to 1BTs, particularly for small block sizes. It is shown that the proposed 2BT-based Motion Estimation technique improves Motion Estimation accuracy in terms of peak signal-to-noise ratio of reconstructed frames and also results in visually more accurate frames subsequent to Motion compensation compared to the 1BT-based Motion Estimation approach.
Jizheng Xu - One of the best experts on this subject based on the ideXlab platform.
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Multi-stage Hash Based Motion Estimation for HEVC
2015 Data Compression Conference, 2015Co-Authors: Wenpeng Ding, Jizheng XuAbstract:Motion Estimation plays an important role in video coding standards, such as H.264/AVC and HEVC. In this paper, we propose a multi-stage hash based Motion Estimation algorithm for HEVC, which enables hash based Motion Estimation for natural videos. In the proposed method, the prediction blocks significantly different from the current prediction unit will be eliminated in the Motion Estimation process. Locality sensitive hashing functions are used to measure the difference between the input block and predicted blocks. The proposed algorithm is implemented into the HM 12.0 software, and the simulation results show that the complexity of Motion Estimation is significantly reduced with negligible coding performance loss.
Ebroul Izquierdo - One of the best experts on this subject based on the ideXlab platform.
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Fast Motion Estimation for surveillance video compression
Signal Image and Video Processing, 2012Co-Authors: Muhammad Akram, Ebroul IzquierdoAbstract:In this article, novel approaches to perform efficient Motion Estimation specific to surveillance video compression are proposed. These includes (i) selective (ii) tracker-based and (iii) multi-frame-based Motion Estimation. In selective approach, Motion vector search is performed for only those frames that contain some Motion activity. In another approach, contrary to performing Motion Estimation on the encoder side, Motion vectors are calculated using information of a surveillance video tracker. This approach is quicker but for some scenarios it degrades the visual perception of the video compared with selective approach. In an effort to speed up multi-frame Motion Estimation, we propose a fast multiple reference frames-based Motion Estimation technique for surveillance videos. Experimental evaluation shows that significant reduction in computational complexity can be achieved by applying the proposed strategies.
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UCMedia - Selective Motion Estimation for Surveillance Videos
Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering, 2009Co-Authors: Muhammad Akram, Naeem Ramzan, Ebroul IzquierdoAbstract:In this paper, we propose a novel approach to perform efficient Motion Estimation specific to surveillance videos. A real-time background subtractor is used to detect the presence of any Motion activity in the sequence. Two approaches for selective Motion Estimation, GOP-by-GOP and Frame-by-Frame, are implemented. In the former, Motion Estimation is performed for the whole group of pictures (GOP) only when moving object is detected for any frame of the GOP. While for the latter approach; each frame is tested for the Motion activity and consequently for selective Motion Estimation. Experimental evaluation shows that significant reduction in computational complexity can be achieved by applying the proposed strategy.
