A forward-facing vision system for a vehicle includes a forward-facing camera disposed in a windshield electronics module attached at a windshield of the vehicle and viewing through the windshield. A control includes a processor that, responsive to processing of captured image data, detects taillights of leading vehicles during nighttime conditions and, responsive to processing of captured image data, detects lane markers on a road being traveled by the vehicle. The control, responsive to lane marker detection and a determination that the vehicle is drifting out of a traffic lane, may control a steering system of the vehicle to mitigate such drifting, with the steering system manually controllable by a driver of the vehicle irrespective of control by the control. The processor, based at least in part on detection of lane markers via processing of captured image data, determines curvature of the road being traveled by the vehicle.

Vision system for vehicle

A vehicular vision system includes a camera having a lens and a CMOS photosensor array having a plurality of photosensor elements. The camera is disposed at an interior portion of a vehicle equipped with the vehicular vision system. The camera one of (i) views exterior of the equipped vehicle through the windshield of the equipped vehicle and forward of the equipped vehicle and (ii) views from the windshield of the equipped vehicle into the interior cabin of the equipped vehicle. A control includes an image processor that processes image data captured by the photosensor array. The image processor processes captured image data to detect an object viewed by the camera. The photosensor array is operable at a plurality of exposure periods and at least one exposure period of the plurality of exposure periods is dynamically variable.

Vehicular vision system

A driver assistance system for a vehicle includes an imaging device having a field of view forward of a vehicle and in a direction of travel of the equipped vehicle, an image processor operable to process image data captured by the imaging device, and a global positioning system operable to determine a geographical location of the vehicle. The equipped vehicle includes an adaptive speed control system for controlling the speed of the equipped vehicle. The adaptive speed control system may reduce the speed of the equipped vehicle responsive at least in part to a detection of a curve in the road ahead of the equipped vehicle via processing by the image processor of image data captured by the imaging device.

Driver assistance system for vehicle

This paper addresses the problem of analyzing human motion in an image sequence. This is of particular importance for video-surveillance applications. We have developed an original and efficient approach to track the apparent contours of a moving articulated structure, avoiding the use of 3D models. This method exploits spatio-temporal XT-slices from the image sequence volume XYT, where typical trajectory patterns can be associated with articulated motion such as human walking. We reconstruct these trajectories online by introducing an appropriate predictive model while correctly handling occlusion periods. This paradigm can lead to a simple trajectory recognition scheme. Experiments with real-world images depicting human walk or gesture are reported, and obtained results validate the proposed approach.

Real-time tracking of moving persons by exploiting spatio-temporal image slices

A vision system for a vehicle includes a first imaging sensor having a first forward field of view and a second imaging sensor spaced from the first imaging sensor and having a second forward field of view, which at least partially overlaps with the first forward field of view. A control processes image data captured by at least one of the first and second imaging sensors to determine an object present in the first and/or second forward fields of view. The control is operable to modulate a headlamp of the vehicle responsive to the processing of image data captured by the at least one of the first and second imaging sensors. The control may process image data captured by both of the imaging sensors to determine a distance between the equipped vehicle and an object present in the overlap of the first and second forward fields of view.

Vehicle vision system

The control system presented in this paper is part of the European Prometheus-ProLab 2 test vehicle which proposes several new significant aids to the driver for an enhanced traffic safety. The goal of this system is to detect and to provide a low-level interpretation of the movements of side-obstacles (vehicles) occurring at crossings. The system is composed of two video cameras and a real-time vision machine (Transvision) on which a specific software performing the obstacle detection and interpretation task has been implemented. The proposed system provides reliable and robust (real-time) control of standard intersections up to a distance of about 150 m.

Y. Ricquebourg

Papers

Real-time collision avoidance at road-crossings on board the Prometheus-ProLab 2 vehicle