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Obstacle detection and tracking is essential module for autonomous driving. Vision based obstacle detection and tracking faces huge challenges due to factors like cluttered background, partial occlusion, inconsistent illumination, etc. In this paper, we propose a robust and low complexity stereo-vision based obstacle detection and tracking framework. Low complexity techniques are employed to detect...
This paper proposes a method to track vehicle in highway using CAMShift-based method. The Continuously Adaptive Mean Shift (CAMShift) is a well-known algorithm in object tracking. However, the ordinary CAMShift works fairly well only for tracking object that can identify by hue, when the difference between object color and background is large. This is not the case in vehicle tracking. The objective...
As an important component of the driver assistance system or autonomous vehicle, traffic sign detection can provide drivers or vehicles with safety and alert information about the road. Most existing methods for traffic sign detection only focus on one or several categories of signs while there are various signs in the real world. This paper proposes a biologically-inspired method for detecting almost...
The authors examine the impact of residential photovoltaic arrays and electric vehicles on distribution transformers by using 3-D surface and 2-D filled contour plots. These visualizations, somewhat unorthodox to power distribution analysis, elucidate the impact of hundreds of assets on distribution transformers on a single view. The visualizations are created with a smart grid computer model that...
In complex urban traffic conditions, occlusion between vehicles is a common problem which is challenging to current vehicle detection methods. In this paper, we have proposed a vehicle detection method based on a part-based model which can deal with the occlusion problem. Our method includes two steps: constructing the part-based model and detecting vehicles from traffic images. In the first step,...
Visual tracking by particle filter with pixel ratio in a region of interest for likelihood computation has wide range of applications despite of its simple algorithm. A GPGPU (General Purpose computation on Graphics Processing Unit) implementation of the visual tracking in parallel computation has been proposed in this paper. Algorithm of the tracker has almost fully been implemented in CUDA framework...
Route backtracking has been applied in many fields, especially in tracing criminal cars. However, because of weak light, shading or shelter, plate numbers are unable to be recognized and the vehicle cannot be traced. So, this paper put forwards a route backtracking method based on video data and road network. the method get routes information by means of vehicles features extraction and matching method...
The exponential growth in the number of web documents and the technological advancements in communication systems over the Internet has resulted in tremendous increase in users accessing those documents for their needs. They may search for documents or for data available in the web. In the former situation, the documents are ranked using different techniques to list the relevant documents in the beginning...
In this paper, we introduce spatiotemporal energy modeling for foreground segmentation in multiple object tracking, a high accuracy and real-time foreground target extraction algorithm. From a single video sequence with multiple moving objects and stationary background, our algorithm combines spatial (color distribution) and temporal (variety between two consecutive frames) information to extract...
Accurate moving objects segmentation is an essential problem in intelligent video surveillance system. However, the existence of unexpected moving cast shadows frequently lead to errors in further scene analysis. This paper presents a novel method that combines color space and corner feature to detect and remove cast shadows of moving vehicles in traffic scenes. The two features cooperate well to...
As urban road intersections are prone to traffic congestion and traffic accidents, monitoring the crossing of vehicles and predicting the state is needed to reduce traffic congestion, regulate driver behavior and prevent accidents. Background subtraction and mean shift tracking are used to track vehicles. The whole monitoring process is as following. Firstly, secondary selected strategy is used to...
Traditional vision based vehicle detection methods are more successful in detecting front and rear vehicles. However, the problem of detecting vehicles under various poses still presents a great deal of difficulty. Pose variation leads to limit the use of vision based driver assistance systems. In this paper, we present a Conditional Random Fields (CRFs) based algorithm that can detect vehicles under...
Various image processing techniques and geometric models have been applied in vision based lane detection subsystems of intelligent vehicles and Advanced Driver Assistance Systems (ADAS). However, challenging conditions such as strong shadows, occlusions, eroded markings, high curvatures are ongoing issues in this topic. In this paper, a novel lane extraction method based on symmetrical local threshold...
Treating visual object tracking as foreground and background classification problem has attracted much attention in the past decade. Most methods adopt mean shift or brute force search to perform object tracking on the generated probability map, which is obtained from the classification results; however, performing probabilistic object tracking on the probability map is almost unexplored. This paper...
At present, vision-based illegally parked vehicles detection faces a range of issues such as narrowness of detection range, low detection precision and robustness. This paper proposed a technique for illegally parked vehicles detection. Firstly, Omni-Directional Vision Sensors (ODVS) are used to access Omni-directional images of the scene. Secondly, a method based on two backgrounds modeled by Gaussian...
Recently video surveillance techniques have been widely applied to intelligent transportation systems. Tracking of moving objects such as vehicles has become a major topic in video surveillance applications. This paper presents a multi-feature fusion model based on a particle filter for moving object tracking. The particle filter combines color and edge orientation information by a stochastic fusion...
This paper addresses the problem of extracting the road region in different driving environments with dynamic lighting changes. Previous approaches using Gaussian mixture models (GMM) have fixed number of models constructed from sample color data and could not keep models associated with shadows. As a result, although they work in some specific environments, they fail in other environments or in scenes...
A shadow detection algorithm base on spatial features was proposed, in the case of focusing on traffic vehicle detection system. First of all, multi-foreground rectangles were extracted by using Gaussian mixture model (GMM) and edge detection operator of mathematical morphology. Then, histogram of horizontal location - foreground point number of vertical direction was computed, combined with optimum...
We have developed a browsing tool for visualizing information about geographic surfaces using map-based augmented reality (AR). Map-based AR technology enables virtual objects to be overlaid on an actual map, creating a tangible user interface. In map-based AR applications, a virtual lens pointer is often used for object selection. However, this type of interaction is difficult when there are many...
Rapid prototyping allows for evaluation of design product in a short period of time. Designers or CEOs may perceive the size and appearance of the product by touching the automatically constructed physical objects produced through rapid prototyping. However, it is usually impossible to change its color, texture, and user interface. In this paper, we introduce 'Augmented Reality based Re-formable Mock-up',...
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