High Resolution satellite Imagery is an important source for road network extraction for urban road database creation, refinement and updating. However due to complexity of the scene in an urban environment, automated extraction of such features using various line and edge detection algorithms is limited. In this paper we present an integrated approach to extract road network from high resoluti...

Road information is essential for automatic GIS (geographical information system) data acquisition, transportation and urban planning. Automatic road (network) detection from high resolution satellite imagery will hold great potential for significant reduction of database development/updating cost and turnaround time. From so called low level feature detection to high level contextsupported gro...

Map matching of GPS trajectories from a sequence of noisy observations serves the purpose of recovering the original routes in a road network. In this work in progress, we attempt to share our experience of feature construction in a spatial database by reporting our ongoing experiment of feature extraction in Conditional Random Fields (CRFs) for map matching. Our preliminary results are obtaine...

Obtaining an accurate vehicle position is important for intelligent vehicles in supporting driver safety and comfort. This paper proposes an accurate ego-localization method by matching in-vehicle camera images to an aerial image. There are two major problems in performing an accurate matching: (1) image difference between the aerial image and the in-vehicle camera image due to view-point and i...

This paper propose an effective approach for detecting and tracking moving vehicles in nighttime traffic scenes. Vehicles were detected automatically from video sequences at nighttime by constructing the MILBoost model. At first, we extract SIFT feature using SIFT feature extraction algorithm, which is used to characterize moving vehicles in nighttime. Then MILBoost model is used for the on-roa...