中国科学院机构知识库网格系统: 检索

Shape Tracking of a Dexterous Continuum Manipulator Utilizing Two Large Deflection Shape Sensors 期刊论文 OAI收割
IEEE Sensors Journal, 2015, 卷号: 15, 期号: 10, 页码: 5494-5503
作者: Liu H(刘浩); Farvardin, Amirhossein; Grupp, Robert; Murphy, Ryan J.; Taylor, Russell H.

收藏 | 浏览/下载：37/0 | 提交时间：2015/08/29

Fiber Bragg grating large curvature shape tracking dexterous continuum manipulator obstacle

基于深度图像的手势交互技术研究 学位论文 OAI收割
工学博士, 中国科学院自动化研究所: 中国科学院大学, 2014
作者: 秦树鑫

收藏 | 浏览/下载：103/0 | 提交时间：2015/09/02

深度图像手势识别运动历史图像凸形状分解三维跟踪粒子群优化并行计算 Depth Image Gesture Recognition Motion History Images Convex Shape Decomposition 3D Tracking Particle Swarm Optimization Parallel Computing

A visual measurement of fish locomotion based on deformable models 会议论文 OAI收割
7th International Conference on Intelligent Robotics and Applications (ICIRA), Guangzhou, PEOPLES R CHINA, DEC 17-20, 2014
作者: Xia, Chunlei(1,2); Li, Yan; Lee, Jang-Myung; Xia, Chunlei

收藏 | 浏览/下载：23/0 | 提交时间：2015/08/10

Fish Active Shape Models Biological studies Deformable models Model-based tracking Observation systems Posture measurement Swimming mode Visual measurements

A visual measurement of fish locomotion based on deformable models 会议论文 OAI收割
The 7th International Conference on Intelligent Robotics and Application (ICIRA2014), Guangzhou, China, December 17-20, 2014.
作者: Xia, Chunlei; Li Y(李岩); Lee, Jang-Myung

收藏 | 浏览/下载：38/0 | 提交时间：2014/12/29

Fish Tracking Model based Tracking Active Shape Model Posture Measurement Swimming Modes

Active Contour-Based Visual Tracking by Integrating Colors, Shapes, and Motions 期刊论文 OAI收割
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2013, 卷号: 22, 期号: 5, 页码: 1778-1792
作者: Hu, Weiming; Zhou, Xue; Li, Wei; Luo, Wenhan; Zhang, Xiaoqin

收藏 | 浏览/下载：37/0 | 提交时间：2015/08/12

Abrupt motion active contour-based tracking adaptive shape model dynamic shape model

Semantic shape similarity-based contour tracking evaluation 期刊论文 OAI收割
OPTICAL ENGINEERING, 2011, 卷号: 50, 期号: 10
作者: Zhang, Xiaoqin; Luo, Wenhan; Zhao, Li; Li, Wei; Hu, Weiming

收藏 | 浏览/下载：29/0 | 提交时间：2015/08/12

evaluation measures contour tracking shape context pyramid match kernels

任意手势的跟踪与识别技术研究 学位论文 OAI收割
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
石磊

收藏 | 浏览/下载：58/0 | 提交时间：2015/09/02

人机手势交互任意手势跟踪手势识别 SVM 隐马尔科夫模型 Gesture based Human Computer Interaction Arbitrary Hand-shape Tracking Hand Postures and Gestures Recognition Support Vector Machine Hidden Markov Model

Rapid and Robust Human Detection and Tracking based on Omega-Shape Features 会议论文 OAI收割
Cairo, Egypt, 7-10 November 2010
作者: Min Li; Zhaoxiang Zhang; Kaiqi Huang; Tieniu Tan

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收藏 | 浏览/下载：17/0 | 提交时间：2016/12/30

Robustness Humans Particle Tracking Target Tracking Head Particle Filters Layout Shape Surveillance Image Edge Detection

Integrated intensity, orientation code and spatial information for robust tracking (EI CONFERENCE) 会议论文 OAI收割
2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007, May 23, 2007 - May 25, 2007, Harbin, China
作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y.

收藏 | 浏览/下载：26/0 | 提交时间：2013/03/25

real-time tracking is an important topic in computer vision. Conventional single cue algorithms typically fail outside limited tracking conditions. Integration of multimodal visual cues with complementary failure modes allows tracking to continue despite losing individual cues. In this paper we combine intensity orientation codes and special information to form a new intensity-orientation codes-special (IOS) feature to represent the target. The intensity feature is not affected by the shape variance of object and has good stability. Orientation codes matching is robust for searching object in cluttered environments even in the cases of illumination fluctuations resulting from shadowing or highlighting etc The spatial locations of the pixels are used which allow us to take into account the spatial information which is lost in traditional histogram. Histograms of intensity orientation codes and spatial information are employed for represent the target Mean shift algorithm is a nonparametric density estimation method. The fast and optimal mode matching can be achieved by this method. In order to reduce the compute time we use the mean shift procedure to reach the target localization. Experiment results show that the new method can successfully cope with clutter partial occlusions illumination change and target variations such as scale and rotation. The computational complexity is very low. If the size of the target is 3628 pixels it only needs 12ms to complete the method. 2007 IEEE.

Intersectant multi-target serial number fuzzy match by multi-parameters (EI CONFERENCE) 会议论文 OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者: Wang Y.-J.

收藏 | 浏览/下载：150/0 | 提交时间：2013/03/25

In order to match the intersectant targets' tab when these objects separate a kind of method that makes use of fuzzy multi-parameter to match targets is proposed. Multi-parameters include the forecasted position after targets separate target speed target size and geometry shape and different parameter corresponds to different influence coefficient evaluate the integrated matching coefficient that every observation target corresponds to forecasted target and the corresponding relationship that matching coefficient is the biggest is the best matching result. In order to locate the position and speed of forecasted target a new method of track forecast is proposed firstly Hough transform is used to the object's track before objects intersect by this the object's positions that the warp between forecasted location and observation location is large enough is eliminated then least square method is used for track forecast by the remainder valid positions and get hold of the forecasted position when objects separate. The experiment results show: when tracking the bulky objects which intersect and separate the right identification probability of traditional least square method is 87.5% and the right identification probability of fuzzy match by multi-parameters can attain 96% the reliability improves in evidence.