Dynamic Building Tracking from UAVs Based on Image Manifold Learning
Fast and accurate visual tracking of ground buildings can provide unmanned aerial vehicles (UAVs) with rich perceptual information,which is very important for target recognition,navigation and system control.However,when an UAV moves fast,both background and buildings in visual scenes change relatively and rapidly.Consequently,there are no constant features for objects appearance,which poses great challenges for visual tracking of buildings.In this paper,we first build an image manifold of buildings,which can encode the continuous variation of appearance.We then propose an efficient approach to learn this manifold and obtain more robust feature extraction results.By using a simple tracking framework,we successfully apply the extracted low-dimensional features to real-time building tracking.Experimental results demonstrate the effectiveness of the proposed method.
manifold learning dynmic visual tracking unmanned aerial vehicles
Peng Zhang Yuanyuan Ren
Data Center National Disaster Reduction Center of China Beijing, 100124, China Department of Hydraulic Engineering Tsinghua University Beijing, 100084, China
国际会议
太原
英文
982-985
2012-12-08（万方平台首次上网日期，不代表论文的发表时间）