A new multimodal RGB and polarimetric image dataset for road scenes analysis

International audience; Road scene analysis is a fundamental task for both autonomous vehicles and ADAS systems. Nowadays, one can find autonomous vehicles that are able to properly detect objects present in the scene in good weather conditions but some improvements are left to be done when the visibility is altered. People claim that using some non conventional sensors (infra-red, Lidar, etc.) along with classical vision enhances road scene analysis but still when conditions are optimal. In this work, we present the improvements achieved using polarimetric imaging in the complex situation of adverse weather conditions. This rich modality is known for its ability to describe an object not o…

POLARIZATION-BASED CAR DETECTION

International audience; Road scene understanding is a vital task for driving assistance systems. Robust vehicle detection is a precondition for diverse applications particularly for obstacle avoidance and secure navigation. Color images provide limited information about the physical properties of the object. This results in unstable vehicle detection caused mainly from road scene complexity (strong reflexions, noises and radiometric distortions). Instead, polarimetric images, characteristic of the light wave, can robustly describe important physical properties of the object (e.g., the surface geometric structure, material and roughness etc). This modality gives rich physical informations wh…

Multimodal Polarimetric And Color Fusion For Road Scene Analysis In Adverse Weather Conditions

The PolarLITIS Dataset: Road Scenes Under Fog

Road scene analysis is a fundamental task for both autonomous vehicles and ADAS systems. Nowadays, one can find autonomous vehicles that are able to properly detect objects in the scene in good weather conditions; however, some improvements still need to be done when the visibility is altered. People claim that using some non-conventional sensors such as, infra-red or Lidar, combined with classical vision, enhances road scene analysis in optimal weather conditions. In this work, we present the improvements achieved using polarimetric imaging in the complex situation of some adverse weather conditions. This rich modality is known for its ability to describe an object not only by its intensit…

Road scenes analysis in adverse weather conditions by polarization-encoded images and adapted deep learning

International audience; Object detection in road scenes is necessary to develop both autonomous vehicles and driving assistance systems. Even if deep neural networks for recognition task have shown great performances using conventional images, they fail to detect objects in road scenes in complex acquisition situations. In contrast, polarization images, characterizing the light wave, can robustly describe important physical properties of the object even under poor illumination or strong reflections. This paper shows how non-conventional polarimetric imaging modality overcomes the classical methods for object detection especially in adverse weather conditions. The efficiency of the proposed …