Object modelling by registration of multiple range images
Image and Vision Computing - Special issue: range image understanding
Building 3-D models from unregistered range images
Graphical Models and Image Processing
An Experimental Comparison of Range Image Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Nonparametric Segmentation of Curves into Various Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Approaches to Large-Scale Urban Modeling
IEEE Computer Graphics and Applications
A bimodal laser-based attention system
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
Globally consistent 3D mapping with scan matching
Robotics and Autonomous Systems
A Bimodal Laser-Based Attention System
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
An attentive, multi-modal laser "eye"
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
Heuristic-based laser scan matching for outdoor 6d SLAM
KI'05 Proceedings of the 28th annual German conference on Advances in Artificial Intelligence
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In this paper, a novel method is presented to generate textured CAD model of out-door urban environment using a vehicle-borne sensor system. In data measurement, three single-row laser range scanners and six line cameras are mounted on a measurement vehicle, which has been equipped with a GPS/INS/Odometer based navigation system. Laser range and line images are measured as the vehicle moves ahead. They are synchronized with the navigation system, so that can be geo-referenced to a world coordinate system. Generation of CAD model is conducted in two steps. A geometric model is first generated using the geo-referenced laser range data, where urban features like buildings, ground surface and trees are extracted in a hierarchical way. Different urban features are represented using different geometric primitives like planar face, TIN and triangle. Texture of the urban features is generated by projecting and re-sampling line images on the geometric model. An out-door experiment is conducted, and a textured CAD model of a real urban environment is reconstructed in a full automatic mode.