Paper Info
Title
Real-time multi-resolution digital elevation map creation using the sensor model of a stereovision sensor.
Abstract
This paper presents an approach for constructing high quality Digital Elevation Maps (DEMs) from dense stereo data. As opposed to classical DEM creation algorithms, the proposed solution uses the sensor models of the stereovision sensor to correct the raw data. The direct and inverse sensor models are found from experiments. The algorithm decomposes the 2D cells containing vertical objects or object boundaries in order to model the objects more precisely. The approach distinguishes between 2 types of cells: cells containing horizontal and vertical objects. For the vertical object cells, connected components in the histogram of heights are found while in the horizontal object cells, the most representative height is determined using a mode-seeking approach similar to mean shift. The 3D reconstructed points are assigned to the cells around it by considering the probability of correspondence based on the 2D Gaussian component of the direct sensor model. In order to eliminate the noise, a similarity measure is computed between each 3D point and cell based on the calculated DEM cell descriptor and is discarded if the similarity score is smaller than a predefined threshold. The algorithm is implemented on the GPU in order to achieve a real-time execution speed and it is evaluated extensively in comparison with other DEM creation algorithms using the latest KITTI stereo benchmark data. The obtained DEM is denser, more accurate and the object boundaries are modeled more precisely.
Year
Venue
Field
2016
ITSC
Iterative reconstruction,Inverse,Computer vision,Histogram,Similarity measure,Simulation,Computer science,Gaussian,Solid modeling,Connected component,Artificial intelligence,Mean-shift
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
szilard mandici121.05
Sergiu Nedevschi21321126.37