NDLI: Multi-modal object detection and localization for high integrity driving assistance

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Multi-modal object detection and localization for high integrity driving assistance

Content Provider	Springer Nature Link
Author	Rodríguez Flórez, Sergio Alberto Frémont, Vincent Bonnifait, Philippe Cherfaoui, Véronique
Copyright Year	2011
Abstract	Much work is currently devoted to increasing the reliability, completeness and precision of the data used by driving assistance systems, particularly in urban environments. Urban environments represent a particular challenge for the task of perception, since they are complex, dynamic and completely variable. This article examines a multi-modal perception approach for enhancing vehicle localization and the tracking of dynamic objects in a world-centric map. 3D ego-localization is achieved by merging stereo vision perception data and proprioceptive information from vehicle sensors. Mobile objects are detected using a multi-layer lidar that is simultaneously used to identify a zone of interest to reduce the complexity of the perception process. Object localization and tracking is then performed in a fixed frame which simplifies analysis and understanding of the scene. Finally, tracked objects are confirmed by vision using 3D dense reconstruction in focused regions of interest. Only confirmed objects can generate an alarm or an action on the vehicle. This is crucial to reduce false alarms that affect the trust that the driver places in the driving assistance system. Synchronization issues between the sensing modalities are solved using predictive filtering. Real experimental results are reported so that the performance of the multi-modal system may be evaluated.
Starting Page	583
Ending Page	598
Page Count	16
File Format	PDF
ISSN	09328092
Journal	Machine Vision and Applications
Volume Number	25
Issue Number	3
e-ISSN	14321769
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2011-12-14
Publisher Place	Berlin/Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Multi-modal perception Visual odometry Object tracking Dynamic map Intelligent vehicles Pattern Recognition Image Processing and Computer Vision Communications Engineering, Networks
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Computer Science Applications Software Hardware and Architecture

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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