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Mine vehicles are a leading cause of mining fatalities. A reliable anti-collision system is needed to prevent vehicle-personnel collisions. The proposed collision detection system uses the fusion of a three-dimensional (3D) sensor and thermal infrared camera for human detection and tracking. In addition to a thermal camera, a distance sensor will provide depth information and allow the calculation...
In this paper we describe a novel approach to model-based monocular vehicle tracking out of a moving vehicle using active vision. The designed algorithm can cope with cluttered color images, complex lighting conditions as well as partial occlusion of the leading vehicle and is able to detect and track a vehicle even within unstructured offroad environments. Thanks to the used 3D model which describes...
This paper presents an application of using geo-data from Lidar and GPS/IMU to detect overpasses. Three characteristics make it a good example of processing large point sets in real-time: a stream paradigm that exploits system parallelism and memory-access coherence, a multi-level detection strategy that distributes computational burden across different operations, and a multi-resolution data structure...
Detecting the parts of a vehicle represents a topic of major interest for computer vision applications, especially for precrash systems. This paper proposes an artificial vision based technique that identifies the pillars of the lateral viewed cars. The novelty of the approach resides in the multi-layer classification scheme applied within the context of a stereo-based object detection system. From...
Alignment of the stereo perception outcomes with the GPS based digital map information is the main goal of this paper. This alignment relies on discriminative sensorial landmarks as stop lines or lane markings and augmented GPS maps. The alignment is needed to provide: an increased accuracy global localization of the static and dynamic detected entities; fusion of the perceived sensorial information...
We present an approach that uses detailed 3D models to detect and classify objects into fine levels of vehicle categories. Unlike other approaches that use silhouette information to fit a 3D model, our approach uses complete appearance from the image. Each 3D model has a set of salient location markers that are determined a-priori. These salient locations represent a sub-sampling of 3D locations that...
This paper presents a generic framework for curb detection and reconstruction in the context of driver assistance systems. Based on a 3D point cloud, we estimate the parameters of a 3D curb model, incorporating also the curb adjacent surfaces, e.g. street and sidewalk. We apply an iterative two step approach. First, the measured 3D points, e.g., obtained from dense stereo vision, are assigned to the...
Newly emerging, highly complex Advanced Driver Assistance Systems (ADAS) fuse the output of various system modules (e.g., lane detection, object classification). Such knowledge fusion is realized in order to gain additional information of the environment allowing for complex system tasks as path planning, the active search for specific objects and task-specific analysis of the environment. As part...
Reliable real-time localization is a key component of autonomous industrial vehicle systems. We consider the problem of using on-board vision to determine a vehicle's pose in a known, but non-static, environment. While feasible technologies exist for vehicle localization, many are not suited for industrial settings where the vehicle must operate dependably both indoors and outdoors and in a range...
Vehicles are indispensable in modern life. The capability of monitoring them over a long range can play significant roles in many surveillance applications. However, due to high mobility of vehicles, tracking them is difficult and we need to utilize a large network of cameras and reason on discrete sets of observations made from non-overlapping cameras. In this paper, we introduce enabling techniques...
There are many approaches to pedestrian detection in collision avoidance systems depending on the sensors (visible light, thermal infrared, radar, laser scanner) used for acquiring the data and the features (depth, shape, motion) used for detection. In this paper we present a method for shape based pedestrian detection in traffic scenes using a stereo vision system for acquiring the image frames and...
Detecting moving objects is a very important aspect of driver assistance systems (DAS). This paper handles this issue by using a vision based system mounted within the vehicle. The pipeline for both a stereoscopic and monocular approach are covered. Both approaches use image sequences and compare moving feature points over time. This sparse information is then segmented using the optimal graph-cut...
We propose a robust object recognition method based on approximate 3D models that can effectively match objects under large viewpoint changes and partial occlusion. The specific problem we solve is: given two views of an object, determine if the views are for the same or different object. Our domain of interest is vehicles, but the approach can be generalized to other man-made rigid objects. A key...
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