机构

• 长春光学精密机械与物... [6]
• 自动化研究所 [4]
• 计算技术研究所 [3]
• 软件研究所 [3]
• 遥感与数字地球研究所 [1]

采集方式

• OAI收割 [17]

内容类型

• 会议论文 [10]
• 期刊论文 [7]

发表日期

• 2025 [2]
• 2022 [2]
• 2020 [1]
• 2019 [1]
• 2016 [1]
• 2012 [1]
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学科主题

• Remote Sen... [1]

筛选

浏览/检索结果: 共17条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择发表日期升序发表日期降序题名升序题名降序提交时间升序提交时间降序作者升序作者降序 Co-ViSu: Accelerating Video Super-Resolution With Codec Information Reuse 期刊论文  OAI收割 IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2025, 卷号: 44, 期号: 9, 页码: 3451-3464 作者:  Fan, Haishuang;  Sun, Qichu;  Wu, Jingya;  Lu, Wenyan;  Li, Xiaowei   |  收藏  |  浏览/下载：2/0  |  提交时间：2025/12/03 Binary sequences  Streaming media  Decoding  Artificial neural networks  Superresolution  Kernel  Engines  Design automation  Video codecs  Throughput  Accelerator  codec  FPGA  super-resolution (SR)   A Joint Visual Compression and Perception Framework for Neuromorphic Spiking Camera 期刊论文  OAI收割 IEEE TRANSACTIONS ON IMAGE PROCESSING, 2025, 卷号: 34, 页码: 4343-4356 作者:  Feng, Kexiang;  Jia, Chuanmin;  Ma, Siwei;  Gao, Wen   |  收藏  |  浏览/下载：3/0  |  提交时间：2025/12/03 Image coding  Cameras  Feature extraction  Encoding  Visualization  Distortion  Decoding  Binary sequences  Video compression  Vectors  Spike compression  visual intelligence  end-to-end spike coding   SANet: Statistic Attention Network for Video-Based Person Re-Identification 期刊论文  OAI收割 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2022, 卷号: 32, 期号: 6, 页码: 3866-3879 作者:  Bai, Shutao;  Ma, Bingpeng;  Chang, Hong;  Huang, Rui;  Shan, Shiguang   |  收藏  |  浏览/下载：73/0  |  提交时间：2022/12/07 Feature extraction  Task analysis  Computational modeling  Visualization  Video sequences  Fuses  Computer science  Person re-identification  self-attention  long-range dependencies  high-order statistics   VidSfM: Robust and Accurate Structure-From-Motion for Monocular Videos 期刊论文  OAI收割 IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 2449-2462 作者:  Cui, Hainan;  Tu, Diantao;  Tang, Fulin;  Xu, Pengfei;  Liu, Hongmin   |  收藏  |  浏览/下载：49/0  |  提交时间：2022/06/06 Cameras  Image reconstruction  Videos  Simultaneous localization and mapping  Video sequences  Robustness  Scalability  Structure from motion  image reconstruction  computational geometry  computer vision   Tangent Fisher Vector on Matrix Manifolds for Action Recognition 期刊论文  OAI收割 IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 3052-3064 作者:  Luo, Guan;  Wei, Jiutong;  Hu, Weiming;  Maybank, Stephen J.   |  收藏  |  浏览/下载：90/0  |  提交时间：2020/04/07 Manifolds  Video sequences  Observability  Videos  Covariance matrices  Kernel  Computational modeling  Action recognition  Fisher vector  Grassmann manifold  Hankel matrix  matrix manifold   Applying maximally stable extremal regions and local binary patterns for guide-wire detecting in percutaneous coronary intervention 期刊论文  OAI收割 IET IMAGE PROCESSING, 2019, 卷号: 13, 期号: 13, 页码: 2579-2586 作者:  Pusit, Prasong;  Xie, Xiao-Liang;  Hou, Zeng-Guang   |  收藏  |  浏览/下载：70/0  |  提交时间：2020/03/30 blood vessels  medical image processing  surgery  image sequences  video signal processing  image filtering  object detection  X-ray imaging  object tracking  stroke width variation filter  region detection  local binary patterns  guide-wire recognition  conventional MSER methods  maximally stable extremal regions  guide-wire position  anatomical skeleton contours  training data  X-ray video sequence  percutaneous coronary intervention surgery  region area range filter  X-ray video monitoring  guide-wire tip detection  modified multifilters  training templates   Validation of MODIS aerosol optical depth retrieval over mountains in central China based on a sun-sky radiometer site of SONET 期刊论文  OAI收割 Remote Sensing, 2016, 卷号: 8, 期号: 2 作者:  Ma, Yan;  Li, Zhengqiang;  Li, Zhaozhou;  Xie, Yisong;  Fu, Qiaoyan 收藏  |  浏览/下载：53/0  |  提交时间：2017/04/24 OBJECT DETECTION  VIDEO SEQUENCES  KERNEL  FEATURES   A simple and fast moving object segmentation based on H.264 compressed domain information (EI CONFERENCE) 会议论文  OAI收割 4th International Conference on Computational and Information Sciences, ICCIS 2012, August 17, 2012 - August 19, 2012, Chongqing, China 作者:  Chen X.;  Chen X.;  Chen X.;  Sun L. 收藏  |  浏览/下载：30/0  |  提交时间：2013/03/25 The paper presents a simple and fast approach for moving object segmentation based on H.264 compressed domain information for the application of indoor video surveillance with static camera. Due to the characteristics of indoor video surveillance  the proposed method of segmentation avoids complicated background model like Gaussian Mixture background model. On the contrary  it chooses some simple information like the type of Macroblock  etc.. Experimental results of several specific H.264 compressed video sequences demonstrate the good segmentation quality of the proposed approach. 2012 IEEE.   Efficient human action recognition using accumulated motion image and support vector machines (EI CONFERENCE) 会议论文  OAI收割 International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2011, November 19, 2011 - November 23, 2011, Suzhou, China 作者:  Zhang X.;  Zhang J.;  Zhang J.;  Zhang X.;  Zhang X. 收藏  |  浏览/下载：86/0  |  提交时间：2013/03/25 Vision-based human action recognition provides an advanced interface  and research in this field of human action recognition has been actively carried out. This paper describes a scheme for recognizing human actions from a video sequences. The proposed method is an extension of the Motion History Image(MHI) method based on the ordinal measure of accumulated motion  which is robust to variations of appearances. We define the accumulated motion image(AMI) using image differences firstly. Then the AMI of the video sequencesis resized to a MN regulation following the standard of training phases. Finally  we employ Support Vector Machine(SVM) as a classifier to distinguish the current activity in target video sequences. In a word  our proposed algorithm not only outperforms the state of art on public available KTH data set and Weizmann data set  but also proves practical to some real world applications  in addition  this method is computationally simple and able to achieve a satisfactory accuracy.   Optimization on motion estimation algorithm based on H. 264 (EI CONFERENCE) 会议论文  OAI收割 2010 3rd International Conference on Advanced Computer Theory and Engineering, ICACTE 2010, August 20, 2010 - August 22, 2010, Chengdu, China Wen X.; Li G. 收藏  |  浏览/下载：76/0  |  提交时间：2013/03/25 Motion estimation is a very important part of video compression. As a result of using precision of motion vector in H.264 encoder  the computational cost increases rapidly  and motion estimation is the most time-consuming stage. In this paper  based on the UMHexagonS algorithm  an optimized algorithm is proposed based on the dynamic search window selection  big hexagon and small hexagon search mode respectively  which saves motion estimation time effectively with a little quality loss. Experiments with some typical video sequences show that compared to the original UMHexagonS algorithm  this new algorithm can save about 17.851 % motion estimation time and reduce the complexity of original scheme as well as enhance the real time performance of encoder and almost has no changes in the reconstructed picture quality and bitrates. 2010 IEEE.