Abstract: Techniques are described for tracking a trailer, including obtaining a sequence of images from a camera positioned in rear of a vehicle, detecting the trailer and a tow-ball in the first image of the sequence of images using a trained learning model based on the first image and at least one scaled version of the first image, estimating an area of interest using a tracking algorithm and locations of the detected trailer and the tow-ball in the first image, estimating a distance between the vehicle and the trailer based on the detected location of the trailer in the first image, and upon determining that the distance between the vehicle and the trailer is less than a second threshold, continuously detecting locations of the trailer, tow-ball and a coupler in each image of the sequence of images using the learning model and the estimated area of interest, and updating the estimated area of interest to correspond to an area of interest in the following image, and actuating an action of the vehicle based on the de

Abstract: Techniques are described for tracking a trailer, including obtaining a sequence of images from a camera positioned in rear of a vehicle, detecting the trailer and a tow-ball in the first image of the sequence of images using a trained learning model based on the first image and at least one scaled version of the first image, estimating an area of interest using a tracking algorithm and locations of the detected trailer and the tow-ball in the first image, estimating a distance between the vehicle and the trailer based on the detected location of the trailer in the first image, and upon determining that the distance between the vehicle and the trailer is less than a second threshold, continuously detecting locations of the trailer, tow-ball and a coupler in each image of the sequence of images using the learning model and the estimated area of interest, and updating the estimated area of interest to correspond to an area of interest in the following image, and actuating an action of the vehicle based on the de

Abstract: A method is disclosed for detecting raised pavement markers in an environment of a vehicle by a camera system. The method includes capturing at least one first image of at least one first part of the environment by at least one first camera of the camera system and analyzing the at least one first image and determining whether at least one first pavement marker is present in the environment in dependency of a result of the analysis of the at least one first image. The method further includes capturing at least one second image of at least one second part of the environment by at least one second camera of the camera system and analyzing the at least one second image and determining whether the at least one first or at least one second pavement marker is present in the environment in dependency of a result of the analysis.

Abstract: A method is disclosed for detecting raised pavement markers in an environment of a vehicle by a camera system. The method includes capturing at least one first image of at least one first part of the environment by at least one first camera of the camera system and analyzing the at least one first image and determining whether at least one first pavement marker is present in the environment in dependency of a result of the analysis of the at least one first image. The method further includes capturing at least one second image of at least one second part of the environment by at least one second camera of the camera system and analyzing the at least one second image and determining whether the at least one first or at least one second pavement marker is present in the environment in dependency of a result of the analysis.