中国开放科研知识云: 检索

Biological Eagle-eye Inspired Target Detection for Unmanned Aerial Vehicles Equipped with a Manipulator 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 5, 页码: 741-752
作者: Yi-Min Deng, Si-Yuan Wang

收藏 | 浏览/下载：2/0 | 提交时间：2023/09/25

Unmanned aerial vehicle (UAV), eagle eye, multi-camera sensor, target detection, saliency detection

A Novel Cooperative Pursuit Strategy in Multiple Underwater robots 会议论文
Marseille, France, June 17-20, 2019
作者: Jia QY(贾庆勇); Xu HL(徐红丽); Feng XS(封锡盛); Gu HT(谷海涛)

收藏 | 浏览/下载：18/0 | 提交时间：2019/12/23

RRT Cooperative pursuit strategy Multiple underwater robots

A Novel Cooperative Pursuit Strategy in Multiple Underwater robots 会议论文
Marseille, France, June 17-20, 2019
作者: Jia QY(贾庆勇); Xu HL(徐红丽); Feng XS(封锡盛); Gu HT(谷海涛)

收藏 | 浏览/下载：4/0 | 提交时间：2019/12/23

RRT Cooperative pursuit strategy Multiple underwater robots

Double mode surveillance system based on remote audio-video signals acquisition 期刊论文
Applied Acoustics, 2018, 卷号: 129, 页码: 316-321
作者: Lv, T.; Zhang, H. Y.; Yan, C. H.

收藏 | 浏览/下载：8/0 | 提交时间：2019/09/17

LDV Laser hearing Voice enhancement Multimodal sensing enhancement laser Acoustics

基于单目视觉的运动目标参数估计 学位论文
工学博士, 中国科学院自动化研究所: 中国科学院大学, 2013
作者: 陈国栋

收藏 | 浏览/下载：45/0 | 提交时间：2015/09/02

打乒乓球机器人视觉测量姿态估计运动特征提取旋转信息估计智能相机 table tennis robot visual measurement pose estimation extraction of movement features rotational information estimation smart camera

面向海量监控视频的智能目标分析与管理系统设计与实现 学位论文
工程硕士, 中国科学院自动化研究所: 中国科学院大学, 2013
董纪超

收藏 | 浏览/下载：46/0 | 提交时间：2015/09/02

视频分析目标检测目标跟踪目标提取目标管理 Video Analysis Object Detection Object Track Object Extraction Object Management

A Method For Moving Target Capture Using 3D Profile Information Based On Bionic Compound Eye 其他
2012-01-01
Luo Bo-Ren; Yan Lei; Liu Hui-Li; Sun Hua-Bo

收藏 | 浏览/下载：2/0 | 提交时间：2015/11/16

bionic compound eye three-dimensional reconstruction moving target detection and capture

A method for moving target capture using 3D profile information based on bionic compound eye 其他
2012-01-01
Luo, Bo-Ren; Yan, Lei; Liu, Hui-Li; Sun, Hua-Bo

收藏 | 浏览/下载：3/0 | 提交时间：2015/11/17

无线视频传感网原型系统设计与实现 学位论文
工学硕士, 中国科学院自动化研究所: 中国科学院研究生院, 2011
作者: 赵学亮

收藏 | 浏览/下载：29/0 | 提交时间：2015/09/02

无线视频传感网 WiFi H.264编码高斯混合模型运动目标检测 WVSN WiFi H.264 Gaussian Mixture Models Moving target detection

The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
Sun H.; Han H.-X.

收藏 | 浏览/下载：50/0 | 提交时间：2013/03/25

Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring precision and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure but in order to capture the change of the state space it need a certain amount of particles to ensure samples is enough and this number will increase in accompany with dimension and increase exponentially this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining" we expand the classic Mean Shift tracking framework.Based on the previous perspective we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information this approach also inhibit interference from the background ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

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