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An approach for the detection of straight and curved curbs (border of relevant traffic isles, sidewalks, etc) is presented, in the context of urban driving assistance systems. A rectangular elevation map is built from 3D dense stereo data. Edge detection is applied to the elevation map in order to highlight height variations. We propose a method to reduce significantly the 3D noise from dense stereo,...
It is known that 93% of accidents occur because of the driver behavioral errors. Many of these can be prevented. Therefore a driver assistance system must include a collision detection component that is capable of generating warnings to prevent an imminent impact and to advise the driver in the traffic scenarios. This paper presents a forward collision warning approach based on a 3D Elevation Map...
An improved approach for the detection of curbs (border of relevant traffic isles, sidewalks, etc) is presented, in the context of urban driving assistance systems. A rectangular elevation map is built from 3D dense stereo data. Edge detection is applied to the elevation map in order to highlight height variations. Temporal filtering is performed for edge points, based on the ego car motion, and only...
A new approach for the detection of curbs (borders of relevant traffic isles, sidewalks, etc) is presented, in the context of urban driving assistance systems. The 3D data from dense stereo is transformed into a rectangular elevation map. The 3D resolution and uncertainty of the stereo sensor are evaluated and used in the detection process. Edge detection is applied on the elevation map in order to...
This paper proposes a new approach for a vehicle based pedestrian detection and classification system. The pedestrian detection is performed based on the 3D data by generating a density map. Pedestrian classification uses a pattern matching approach and exploits both 2D image information and 3D dense stereo information. Because 3D information accuracy does not allow the direct classification of the...
A new approach for the detection of the road surface and obstacles is presented. The 3D data from dense stereo is transformed into a rectangular elevation map. A quadratic road surface model is first fitted, by a RANSAC approach, to the region in front of the ego vehicle. This primary solution is then refined by a region growing-like process, driven by the 3D resolution and uncertainty model of the...
This paper presents a lane detection system that combines stereovision-specific techniques with grayscale image processing for maximizing the robustness and applicability against the difficult conditions of the urban environment. The lane marking features are extracted using a fast and robust dark-light-dark transition detector that's aware of the perspective effect. The clothoid lane model is matched...
This paper presents an algorithm for tracking the cuboids generated from grouping the 3D points obtained through stereovision. The solution described in the paper takes into consideration the particularities of the scenario and of the sensor, and brings considerable improvement in all the phases of tracking: initialization, prediction, measurement and update. The corner of the cuboid becomes the central...
The urban driving environment is a complex and demanding one, requiring increasingly complex sensors for the driving assistance systems. These sensors must be able to analyze the complex scene and extract all the relevant information, while keeping the response time as low as possible. The sensor presented in this paper answers to the requirements of the urban scenario through a multitude of detection...
This paper presents a monocular night vision system specifically developed for detecting very distant pedestrians. The focus of the system is the recognition of pedestrians that are between 40 and 100 m away from the camera. The system is intended to integrate with an existing system, which is capable of detecting pedestrians at distances less than 40 m. At very large distances, pedestrians appear...
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