Real-time automotive street-scene mapping through fusion of improved stereo depth and fast feature detection algorithms

The real-time tracking of street scenes as a vehicle is driving is a key enabling technology for autonomous vehicles. In this work we provide the basis for such a system through combining an improved advanced random walk with restart technique for stereo depth determination with fast, robust feature...

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Bibliographic Details
Published inProceedings of IEEE International Symposium on Consumer Electronics pp. 225 - 228
Main Authors Javidnia, Hossein, Corcoran, Peter
Format Conference Proceeding
LanguageEnglish
Published IEEE 2017
Subjects
Benchmark testing
Cameras
Conferences
Feature extraction
Real-time systems
Roads
Three-dimensional displays
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ISSN2158-4001
DOI10.1109/ICCE.2017.7889293

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Summary:The real-time tracking of street scenes as a vehicle is driving is a key enabling technology for autonomous vehicles. In this work we provide the basis for such a system through combining an improved advanced random walk with restart technique for stereo depth determination with fast, robust feature detection. The enables tracking and mapping of a wide range of scene structures which can be readily resolved into individual objects and scene elements. Thus it is practical to identify moving objects such as vehicles, pedestrians and fixed objects and structures such as buildings, trees and roadside kerb.
ISSN:2158-4001
DOI:10.1109/ICCE.2017.7889293