The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
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...
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...
In this paper, we present an effective and robust visual vehicle tracking algorithm using particle filter and multiple cues. A stable histogram-based framework is extended to evaluate color, edge, texture and motion cues in structured environments. This framework is suitable for practical conditions since in many applications the object motions are limited by structure of the surveillance scene. We...
We present a system to perform video analysis in the context of traffic surveillance's application. A training step is performed to estimate the scene's geometry and global information about the motion that occurs in the scene. Lanes boundaries, depth and motion information given by the initialization step are used to assist the vehicles' segmentation and to correct eventual errors.
Within a surveillance video, occlusions are commonplace, and accurately resolving these occlusions is key when seeking to accurately track objects. The challenge of accurately segmenting objects is further complicated by the fact that within many real-world surveillance environments, the objects appear very similar. For example, footage of pedestrians in a city environment will consist of many people...
Illumination change usually results in challenging problems for many computer vision applications such as recognition, tracking and motion analysis. In this paper, an illumination invariant object tracking approach is proposed. Video feature information is captured using a monogenic scale space representation. From this representation, multiscale phase information, which has the advantage of being...
In this paper, we propose a vehicle detection and tracking algorithm. The detection is done using the median filtering and blob extraction. Median filtering is used for background extraction which is later subtracted from the motion frames for object detection. Morphological operators are employed for blob extraction. Hence, object detection is achieved using median filtering and morphological closing...
Forewarning to avoid potential traffic accidents is of great importance for Intelligent Transportation Systems (ITS). Under pedestrian and vehicle mixed traffic conditions like urban road intersections, traffic monitoring and forewarning have especially important values. Therefore in this paper a novel urban traffic information analysis and forewarning system is presented. Our system contains modules...
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...
Object tracking using vision technology is one of the key but complex functions in navigation system of Intelligent Vehicles; it became more difficult in case of there are partial occlusions and significant clutter. A mean shift embedded approach is presents for vehicle tracking under real road scenes. The HSI model and orientation histogram are used to represent the object feature; the mean shift...
This article presents a laboratory computer vision system for vehicle detection and tracking. Vehicles are marked with colored circles, that are detected by the presented computer vision system. Detection of targets is performed by their shape using circular Hough transform. Once the locations of the targets are known, their colors are acquired. Tracking of the targets through video frames is then...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.