IEEE Transactions on Pattern Analysis and Machine Intelligence

Developing on-board automotive driver assistance systems aiming to alert drivers about driving environments, and possible collision with other vehicles has attracted a lot of attention lately. In these systems, robust and reliable vehicle detection is a critical step. This paper presents a review of recent vision-based on-road vehicle detection systems. Our focus is on systems where the camera is mounted on the vehicle rather than being fixed such as in traffic/driveway monitoring systems. First, we discuss the problem of on-road vehicle detection using optical sensors followed by a brief review of intelligent vehicle research worldwide. Then, we discuss active and passive sensors to set the stage for vision-based vehicle detection. Methods aiming to quickly hypothesize the location of vehicles in an image as well as to verify the hypothesized locations are reviewed next. Integrating detection with tracking is also reviewed to illustrate the benefits of exploiting temporal continuity for vehicle detection. Finally, we present a critical overview of the methods discussed, we assess their potential for future deployment, and we present directions for future research.

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On-road vehicle detection: a review

This paper provides a review of the literature in on-road vision-based vehicle detection, tracking, and behavior understanding. Over the past decade, vision-based surround perception has progressed from its infancy into maturity. We provide a survey of recent works in the literature, placing vision-based vehicle detection in the context of sensor-based on-road surround analysis. We detail advances in vehicle detection, discussing monocular, stereo vision, and active sensor-vision fusion for on-road vehicle detection. We discuss vision-based vehicle tracking in the monocular and stereo-vision domains, analyzing filtering, estimation, and dynamical models. We discuss the nascent branch of intelligent vehicles research concerned with utilizing spatiotemporal measurements, trajectories, and various features to characterize on-road behavior. We provide a discussion on the state of the art, detail common performance metrics and benchmarks, and provide perspective on future research directions in the field.

https://cvrr.ucsd.edu/publications/2013/SayananTrivedi_IEEETITS2013_VehicleSurvey.pdf

Looking at Vehicles on the Road: A Survey of Vision-Based Vehicle Detection, Tracking, and Behavior Analysis

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

An object recognition system including a position sensor, an image sensor and a controller is provided. The position sensor determines the position of an object, and the image sensor captures an image of the object. The controller sets a processing area within the image captured by the image sensor based on the position of the object determined by the position sensor and a predetermined size for the object to be recognized. The controller extracts horizontal edges from the processing area, and identifies horizontal edges belonging to the outline of the object from the extracted edges. Thus, the object can be recognized based on the horizontal edges only. Similarly, the controller can extract vertical edges from the processing area and identify vertical edges belonging to the outline of the object. Preferably, the controller selects upper, lower, left, and right horizontal and vertical candidate ends of the object from the identified horizontal and vertical edges respectively, from which upper, lower, left, and right ends of the object are determined. If either one or both of the left and right horizontal candidate ends cannot be selected, candidate ends can be estimated based on the position of the object recognized in a previous recognition cycle, and the estimated candidate ends can be used in lieu of the candidate ends selected from the horizontal edges.

Object recognition system

An object detection system comprises a physical object recognition unit which recognizes physical objects outside the vehicle, and a physical object memory which stores information concerning the physical objects. A controller recognizes presence of a physical object when the physical object is sensed by one or more sensors a predetermined number of times, which is larger for a central portion of the detecting area than for a peripheral portion of the detecting area. The system includes a memory for storing information about the physical objects. The controller holds the physical object stored in the memory indicating that the physical object is existent until the controller fails to recognize presence of the corresponding physical object a predetermined number of recognition cycles.

Object detection system

Provided is a vehicle surroundings monitoring device. Specifically, provided is a surroundings monitoring device mounted on a vehicle and equipped with: an infrared camera which images the surroundings of the vehicle; a display means for generating a display image on the basis of the image data imaged by means of the infrared camera and for displaying said display image; a calibration means for calibrating the output between the pixels of the infrared camera on the basis of the image data which imaged the surface of a shutter for opening and closing the aperture through which light enters to the infrared camera; an estimation means for estimating the stability of the temperature of the infrared camera from the operating condition of the vehicle; and a determination means for determining, on the basis of the behavior of the vehicle, the likelihood that the driver is viewing the display means. The calibration means performs calibration when it is estimated that the temperature of the infrared camera is stable and when it is determined that the likelihood that the driver is viewing the display means is low.

Vehicle surroundings monitoring device

An object recognition system comprises a memory for storing a plurality of distance ranges with different distance labels associated with respective distance ranges. The controller converts measured distance values into distance labels according to distance ranges to which the distance values belong. The controller groups the sections or windows of a captured image based on assigned distance labels. Detection area or viewing area of the sensors is divided into a plurality of distance ranges according to tolerance of the measured distance such that broader distance range is defined as the distance from the system is larger. The controller scans the windows with distance labels using a template that defines a joining relationship for the windows and assigns each window with a cluster label that is a combination of the distance label and a occurrence indicia, which is the same for the windows that satisfy the joining relationship. The controller unites the windows having the same cluster labels into a cluster, generates three dimensional data of each of said clusters and combines the clusters that are positioned close to each other based on the three dimensional data to form a candidate of a physical object. The system includes a memory for storing three dimensional data of one or more physical objects that were recognized in previous recognition cycle. The controller infers a physical object which would be recognized in the current cycle based on the stored data and a speed of the vehicle relative to the physical object. The controller compares the inferred physical object with said candidate of a physical object to recognize a physical object.

Optical object recognition system

PROBLEM TO BE SOLVED: To exactly discriminate the relative positions of an object and a present vehicle travel line SOLUTION: Concerning the object recognizing device provided with a radar for specifying the position of the object and an image pickup device for picking up the image of the object, the position of the present vehicle travel line is detected on the basis of the image provided by the image pickup device Further, a processing area is set onto the image provided by the image pickup device on the basis of the specified position of the object and the predetermined size of the object to be recognized, an edge is extracted from the processing area on the basis of the luminance value of pixels contained in the processing area, and the outer form of the object is recognized on the basis of the extracted edge On the basis of the information of the recognized outer form of the object and the detected position of the present vehicle travel line, the relative position of this object corresponding to the present vehicle travel line is discriminated Since the position and size of the object can be exactly recognized, the relative position of the object to the present vehicle travel line can be exactly judged COPYRIGHT: (C)2001,JPO

Morimichi Nishigaki

Papers

Object recognition system

Object detection system

Vehicle surroundings monitoring device

Optical object recognition system

Object recognizing device