Abstract:
A method for determining a wet surface condition of a road. Capturing an image of a wheel of a remote vehicle traveling in an adjacent lane by an image capture device of a host vehicle. Identifying in the captured image, by processor of a host vehicle, a region of interest relative to the wheel where the region of interest is representative of where precipitation dispersion occurs. A determination is made whether precipitation is present in the region of interest. A wet road surface signal is generated in response to the identification of precipitation in the adjacent lane.
Abstract:
A method for determining a wet surface condition of a road. An image of a road surface is captured by an image capture device of the host vehicle. The image capture device is mounted on a side of the host vehicle and captures an image in a downward direction. A region of interest rearward of the wheel of the host vehicle is identified in the captured image by a processor. The region of interest is representative of where rearward splash as generated by the wheel occurs. A determination is made whether precipitation is present in the region of interest by applying a filter to the image. A wet road surface signal is generated in response to the identification of precipitation in the region of interest.
Abstract:
Techniques for road scene primitive detection using a vehicle camera system are disclosed. In one example implementation, a computer-implemented method includes receiving, by a processing device having at least two parallel processing cores, at least one image from a camera associated with a vehicle on a road. The processing device generates a plurality of views from the at least one image that include a feature primitive. The feature primitive is indicative of a vehicle or other road scene entities of interest. Using each of the parallel processing cores, a set of primitives are identified from one or more of the plurality of views. The feature primitives are identified using one or more of machine learning and classic computer vision techniques. The processing device outputs, based on the plurality of views, result primitives based on the plurality of identified primitives from multiple views based on the plurality of identified entities.
Abstract:
A vehicle imaging system includes an image capture device capturing an image exterior of a vehicle. The captured image includes at least a portion of a sky scene. A processor generates a virtual image of a virtual sky scene from the portion of the sky scene captured by the image capture device. The processor determines a brightness of the virtual sky scene from the virtual image. The processor dynamically adjusts a brightness of the captured image based the determined brightness of the virtual image. A rear view mirror display device displays the adjusted captured image.
Abstract:
A method for determining a wet road surface condition for a vehicle driving on a road. An image exterior of the vehicle is captured by an image capture device at a first and second instance of time. Potential objects and feature objects are detected on a ground surface of the road of travel at the first instance of time and the second instance of time. A determination is made whether the ground surface includes a mirror effect reflective surface based on a triangulation technique utilizing the feature points in the captured images at the first instance of time and the second instance of time. A wet driving surface indicating signal is generated in response to the determination that the ground surface includes a mirror effect reflective surface.