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Geoinformation inventories are often employed as a tool for providing a comprehensive view onto the required state of traffic control infrastructure. They are especially important in road safety inspection where, in combination with georeferenced video, they enable repeatable off-line and off-site assessments as an attractive alternative to classic onsite inspection. Nevertheless, manual assessments...
Unsupervised learning of semantic activities from video collected over time is an important problem for visual surveillance and video scene understanding. Our goal is to cluster tracks into semantically interpretable activity models that are independent of scene locations; most previous work in video scene understanding is focused on learning location-specific normalcy models. Location-independent...
Ground-truth data is essential for the objective evaluation of object detection methods in computer vision. Many works claim their method is robust but they support it with experiments which are not quantitatively assessed with regard some ground-truth. This is one of the main obstacles to properly evaluate and compare such methods. One of the main reasons is that creating an extensive and representative...
Road Sign Detection is a major goal of Advanced Driving Assistance Systems (ADAS). Since the dawn of this discipline, much work based on different techniques has been published which shows that traffic signs can be first detected and then classified in video sequences in real time. While detection is usually performed using classical computer vision techniques based on color and/or shape matching,...
Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community. In order to execute a safe navigation on outdoors it is necessary to identify parts of the terrain that can be traversed by the robot and parts that should be avoided. This paper describes an analyses of an image-based terrain identification based on different visual information features....
This paper presents a real-time implementation on lane detection and tracking system in order to localize lane boundaries and estimate a linear-parabolic lane model. It is realized using TMS320DM642 DSP board. Video frame is first captured with CCD camera and stored in video port buffer. Next, input image is split into sky and road region with horizon localization. Lane analysis is applied on the...
On the basic of the video traffic surveillance system, the Vehicle detection is a crucial step. A typical method is background subtraction. Extracting and updating the background plays an important role on speed and efficiency of detection. For this reason, the author puts forward a fast and effective method for building and updating the background model. First, adopt the improved statistical method...
Median value filter is used to eliminate or reduce the noise caused by the outside environment. The edge information of road image is enhanced by Sobel operator. And then based on the Otsu method, an effective algorithm is proposed to binary-code the lane image in order to segment and identify road edge easily. Finally, Hough transformation is used to extract the feature of lane and detect the lane...
The research of red light runners video detecting algorithm is an important research field in computer vision applications. This paper proposes a novel method for red light runners video detecting based on analysis of tracks of vehicles. This method including two steps: obtaining and fit for tracks of vehicles and analysis of red light runners. Our method is simple and effective, as while as can be...
In this paper, we present a robust road detection and tracking method based on a condensation particle filter for real-time video-based navigation applications. The image is divided into horizontal strips, and vanishing point (VP) detection is performed on each image strip. We propose a method for estimating the density of road boundary line segments in the image so that VP detection in an image strip...
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