This paper describes a multimodal vision sensor that integrates three types of cameras, including a stereo camera, a polarization camera and a panoramic camera. Each sensor provides a specific dimension of information: the stereo camera measures depth per pixel, the polarization obtains the degree of polarization, and the panoramic camera captures a 360° landscape. Data fusion and advanced environment perception could be built upon the combination of sensors. Designed especially for autonomous driving, this vision sensor is shipped with a robust semantic segmentation network. In addition, we demonstrate how cross-modal enhancement could be achieved by registering the color image and the polarization image. An example of water hazard detection is given. To prove the multimodal vision sensor’s compatibility with different devices, a brief runtime performance analysis is carried out.
A multimodal vision sensor for autonomous driving
Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies III ; 2019 ; Strasbourg,France
Proc. SPIE ; 11166
2019-10-07
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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