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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...
Vehicle detection and tracking plays an effective and significant role in the area of traffic surveillance system where efficient traffic management and safety is the main concern. In this paper, we discuss and address the issue of detecting vehicle / traffic data from video frames. Although various researches have been done in this area and many methods have been implemented, still this area has...
In this paper, we propose a novel vehicle tracking system under a surveillance camera. The proposed system tracks vehicles by using constrained multiple-kernel facilitated with Kalman filtering, and then continuously updates the position and the orientation by adopting a systematically built 3-D vehicle model in an evolutionary computing framework. The proposed system can thus successfully track vehicles...
This paper presents a new method to track and count vehicles in video traffic sequences. The proposed method uses image processing, particle filtering, and motion coherence to group particles in videos, forming convex shapes that are analyzed for potential vehicles. This analysis takes into consideration the convex shape of the objects and background information to merge or split the groupings. After...
Nowadays, vehicle tracking is a vital approach to assist and improve the road traffic control, surveillance and security systems by having the detail of the captured vehicle information. In past, many tracking techniques have been implemented and suffered from the well known 'occlusion' problems. Increasing the accuracy of the tracking algorithm has caused the computational cost due to the inflexibility...
In this paper, we address the problem of vehicle detection and tracking with low-angle cameras by combining windshield detection and feature points clustering, effectively fusing several primitive image features such as color, edge and interest point. By exploring various heterogenous features and multiple vehicle models, we achieve at least two improvements over the existing methods: higher detection...
In this paper we propose a multi sensor tracking method. Tracking is done independently for each view. Fusing several cues including color, edge, texture and motion constrained by structure of environment is used in a novel way. Fusion of features in particle filter framework helps to achieve an accurate tracking algorithm in single view. The results of individual image planes are projected to the...
The vehicle shadow's detection and elimination work basically for extracting and tracking the vehicle characteristics, and it also plays a very important role in highway video surveillance and incident detection, affecting the post-processing of video image directly, such as vehicle tracking and speed measurement. On study of Kimmel variational and multi-scale Retinex algorithm to eliminate the vehicle...
This paper proposed an accurate shadow removal method for vehicle tracking. Firstly we detect and remove the shadow using optical gain based gradient analysis,in this process some parts of vehicle which are similar to shadow region in color space may be detected as shadow and removing these parts will leave some holes in the vehicle region. Then we fill these holes using the skeleton information of...
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...
Because when moving objects are tracked by mean-shift algorithm, the starting position of target in the current frame starts at the center of the target in the previous frame, so the accuracy of vehicle tracking is not too high. In order to overcome this shortcoming, the mask-based mean-shift algorithm is proposed in the paper. The accuracy of target tracking can be improved by forecasting its starting...
Real-time image processing is a difficult work for traffic video monitoring. This paper proposed a method to detect and track vehicles on highway based on airship video and therefore calculate traffic parameters in real-time. A blocking road extraction was performed to determine the ROI, and automatically calculate the tilt of the road which contributes to vehicles detection. A lane marks registration...
In modern intelligent transportation systems, the video image vehicle detection system (VIVDS) is gradually becoming one of the popular methods at signalized traffic intersection due to its convenient installation and rich information content provided. However, in the current VIVDS, the camera usually is installed at the roadside poles or traffic light poles, which not only requires more than one...
Delay of signalized intersection has been estimated not only by manual method but also some intersection models. Long queues of lanes will make it difficult for collecting data manually and delay calculated by signalized intersection models may not be perfect for a particular intersection. In this paper, we design a system that can calculate delay automatically based on image processing technology...
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...
Video-based surveillance and measuring have been employed more and more widely in traffic monitoring system because of the rich information content contained in video. The vehicles need to be segmented from the video images, the result of vehicles segmentation using background subtraction is not only vehicles but also shadows of vehicles, a method of shadow removing based on texture analysis is presented...
Developing real-time traffic parameters surveillance systems based on video aiming to extract reliable traffic state information has attracted a lot of attention during the past decades. These traffic state parameters include traffic flow density, the length of queue, average traffic speed and total vehicle in fixed time intervals. In these systems, robust and reliable vehicle detection and tracking...
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