Highway 3D model from image and lidar data

Jinfeng Chen; Henry Chu; Xiaoduan Sun

doi:10.1117/12.2054437

22 May 2014 Highway 3D model from image and lidar data

Jinfeng Chen, Henry Chu, Xiaoduan Sun

Proceedings Volume 9118, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XII; 91180E (2014) https://doi.org/10.1117/12.2054437
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

We present a new method of highway 3-D model construction developed based on feature extraction in highway images and LIDAR data. We describe the processing road coordinate data that connect the image frames to the coordinates of the elevation data. Image processing methods are used to extract sky, road, and ground regions as well as significant objects (such as signs and building fronts) in the roadside for the 3D model. LIDAR data are interpolated and processed to extract the road lanes as well as other features such as trees, ditches, and elevated objects to form the 3D model. 3D geometry reasoning is used to match the image features to the 3D model. Results from successive frames are integrated to improve the final model.

Citation Download Citation

Jinfeng Chen, Henry Chu, and Xiaoduan Sun "Highway 3D model from image and lidar data", Proc. SPIE 9118, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XII, 91180E (22 May 2014); https://doi.org/10.1117/12.2054437

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