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The Microsoft Kinect device is capable to perform object detection using its advanced depth sensors. In this project, the Kinect depth sensor is used for object detection for vehicle collision avoidance. Tests performed on several types of vehicles and environmental conditions indicate that the Kinect sensor is able to perform this task well under various conditions.
In urban environments, detection of moving obstacles and free space determination are key issues for driving assistance systems or autonomous vehicles. This paper presents a lidar-based perception system for passenger-cars, able to do simultaneously mapping and moving obstacles detection. Nowadays, many lidars provide multi-layer and multi-echo measurements. A smart way to handle this multi-modality...
This paper presents an algorithm for obstacle classification and lane line identification using the laser range finder (LRF) sensors, which is used to warn the driver to watch the situation of environment when the obstacle appear in the front. The classification of detecting objects is essential to reduce the danger in traffic. Nevertheless, there may be a noise (or road surface) in far distance....
An obstacle detection and tracking system using a 2D laser sensor and the Kalman filter is presented. This filter is not very efficient in case of severe disturbances in the measured position of the obstacle, as for instance, when an object being tracked is behind a barrier, thus interrupting the laser beam, making it impossible to receive the sensor information about its position. This work suggests...
This paper presents a method to solve the correspondence problem in matching the stereo image using Sum of Absolute Differences (SAD) algorithm. The computer vision application in this paper is using an autonomous vehicle which has a stereo pair on top of it. The estimation of range is using curve fitting tool (cftool) for each detected object or obstacles. This tool is provided by Matlab software...
In this paper, a new type of autonomous vehicle is developed. This vehicle consists of three sets of control systems to regulate the direction, brake and fuels. The sensing system is a combination of laser radar and camera. The localization system is constructed with GPS device and electronically compass. Currently, three tasks, including lane detection and following, object detection, and obstacle...
The video-based on-road detection of vehicles at daytime allows driver assistance systems to avoid collisions and thereby improve safety, and realize comfort functions, like the well known adaptive cruise control. However, at nighttime, common video sensor based vehicle detection algorithms can't be used, because most state-of-the-art features, like shadows, symmetry and others, cannot be measured...
Several premium automotive brands offer night vision systems to enhance the driver's ability to see at night. Most recent generation night vision systems have added pedestrian detection as a feature to assist drivers to avoid potential collisions. This paper reviews pedestrian detection based on two different sensing technologies: active night vision operating in the near-infrared (NIR) region of...
Lots of rear end collisions due to driver inattention have been identified as a major automotive safety issue. A short advance warning can reduce the number and severity of the rear end collisions. This paper describes a Forward Collision Warning (FCW) system based on monocular vision, and presents a new vehicle detection method: appearance-based hypothesis generation, template tracking-based hypothesis...
The Contextual Visual Dataspace (CVD) is a real-time representation of an automotive environment that combines automated 3D modeling and semantic labeling of a scene with dynamic object detection using infrastructure cameras. Our automotive active safety concept uses CVD to detect and track dynamic objects of interest, geo-register them into the semantically labeled 3D world space, analyze the paths...
This paper describes a framework which uses augmented reality for evaluating the performance of mobile computer vision systems. Computer vision systems use primarily image data to interpret the surrounding world, e.g to detect, classify and track objects. The performance of mobile computer vision systems acting in unknown environments is inherently difficult to evaluate since, often, obtaining ground...
The robust and reliable detection of objects in the surrounding of a vehicle is an important prerequisite for collision avoidance and collision mitigation systems. In this paper, an ego-motion compensated tracking approach is presented which uses extended occupancy grid methods for both detection and tracking of objects observed by lidar. The approach is able to estimate the velocity and direction...
Stand-alone cameras or CCTV networks are nowadays commonly present in public areas such as city centers, stores and more recently in transportation infrastructures. In the meantime, automatic processing of video data is a field of activity stirring up the utmost attention in the pattern recognition community; state-of-the-art advances in this area enable the reliable extraction of features and the...
The practical driving safety assistant system should be able to estimate the possibility of pedestrian-vehicle collision, which includes pedestrian detection and localization as well as collision prediction. Until now, many works concentrated on pedestrian detection and achieved some progress. For collision prediction, it is essential to locate the pedestrian precisely; however, the localization problem...
Making full uses of the processing performance and peripheral features of DSP TMS320DM6437 chip, we innovatively designed a vehicle collision avoidance system with low-cost, high reliability. The system can achieve functions of vehicle detection, vehicle distance measurement and auto-assisted control. Through simulations and experiments, we verified the correctness of the system's hardware platform,...
The lobula giant movement detector (LGMD) is a wide-field visual neuron that is located in the lobula layer of the locust nervous system. The LGMD increases its firing rate in response to both the velocity of the approaching object and its proximity. It has been found that it can respond to looming stimuli very quickly and can trigger avoidance reactions whenever a rapidly approaching object is detected...
The driving support is one of the most important research areas in intelligent transport system (ITS). Moreover, obstacle extraction system is one of most important system. Here, baseline length of our stereovision system is shorter than general one so that the room mirror can cover it. Accordingly, it can be placed unobtrusively and never be unsighted for the driver. Therefore, our stereovision system...
The driving support is one of the most important research areas in intelligent transport system (ITS). Moreover, obstacle extraction system is one of most important system. Here, baseline length of our stereovision system is shorter than general one so that the room mirror can cover it. Accordingly, it can be placed unobtrusively and never be unsighted for the driver. Therefore, our stereovision system...
Autonomous robot navigation has many applications such as space exploration and autonomous vehicles. Currently, such navigation is ensured by the use of multiple sensors which may hinder quick commercialization. In this article, we propose a solution for navigating a robot in an unknown environment using only monocular vision algorithms.
The robust and reliable detection of objects in the path of a vehicle is an important prerequisite for collision avoidance and collision mitigation systems. In this paper, an ego-motion compensated tracking approach is presented which combines radar observations with the results of a contour-based image processing algorithm. The approach is able to handle all uncertainties of the system in a unified...
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