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In this paper we propose an approach for dynamic scene perception from a moving vehicle equipped with a stereo camera rig. The approach is solely based on visual information, hence it is applicable to a large class of autonomous robots working in indoor as well as in outdoor environments. The proposed approach consists of an egomotion estimation based on disparity and optical flow using the Longuet-Higgins-Equations...
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...
A new method for real-time detection and tracking of multiple moving vehicles from traffic video is proposed. This method first uses MoG and texture based model to extract foreground from the scene, then detect moving targets using a modified version of timed motion history image (tMHI), and finally uses Kalman prediction filter to track these targets, which the full moving trajectories of the targets...
For an autonomous vehicle, detecting and tracking other vehicles is a critical task. Determining the orientation of a detected vehicle is necessary for assessing whether the vehicle is a potential hazard. If a detected vehicle is moving, the orientation can be inferred from its trajectory, but if the vehicle is stationary, the orientation must be determined directly. In this paper, we focus on vision-based...
In this paper, a general algorithm for pedestrian detection by on-board monocular camera which can be applied to cameras of various view ranges in unified manner. The Spatio-Temporal MRF model extracts and tracks foreground objects as pedestrians and non-pedestrian distinguishing from background scenes as buildings by referring to motion difference. During the tracking sequences, cascaded HOG classifiers...
In this paper we propose an automatic vehicle tracking method for monitoring traffic intersections. The method uses a weighted combination of low-level features and low-level human-visual-system (HVS) modeling. Given an input video, moving vehicles are first detected from the scene and low-level features are extracted from the detected vehicles. Next, each detected region in the current video frame...
As traffic surveillance technologies continue to grow worldwide, vehicle detection, counting and tracking are becoming increasing important. This paper proposes a real-time multi-vehicle detection and tracking approach. Lane marker detection is carried out for vehicle counting on each lane. It also helps remove the foreground noise and shadow. Instead of tracking the entire vehicle blob, vehicle sub-feature...
In this paper, we formulate the feature clustering problem for vehicle detection and tracking as a general MAP problem and solve it using MCMC. The proposed approach exhibits two advantages over existing methods: general Bayesian model can handle arbitrary objective functions and MCMC guarantees global optimal solution. Our algorithm is validated on real-world traffic video sequences, and is shown...
Due to the recent progress in computer vision to interpret images and sequence of images, the video camera is a promising sensor for traffic monitoring and traffic surveillance at low cost. This paper focuses on the detection and tracking of multiple vehicles present in the field of view of a camera. Until now, the vehicle detection has been mainly performed by the widely used technique called background...
This study presents an effective system for detecting and tracking moving vehicles in nighttime traffic scene for traffic surveillance. The proposed method identifies vehicles based on detecting and locating vehicle headlights and taillights by using the techniques of image segmentation and pattern analysis. First, to effectively extract bright objects of interest, a fast bright-object segmentation...
One key goal of current Computer Vision research activities is to provide robust systems for improving Transport safety through the use of Information Technology. Recent advances allow public environments (such as train stations or, simply, the street) under video surveillance to be modelled by means of the detection, tracking, and identification of the different elements in it (passengers, road,...
A novel strategy for the visual tracking and the information extracted problem is proposed which is for the case of maneuvering target. The strategy contains two methods. One is used to tracking, and the other one is used to extract the information of the vehicle. A non-linear estimation method using the particle filter to track objects is presented. During the tracking, a great deal of vehicle information...
A vehicle detection algorithm was proposed based on the morphology and wavelet transform, in the context of the traditional difference. First, the background model was established, using statistical means of the rapid sequence. As background to transform the impact of light obviously, the corresponding easy and quick to update the background algorithm was used. Using the background of the video images...
Vehicle tracking is a challenging problem in Intelligent Transport System. This paper presents a vehicle tracking approach combining blob based tracking and feature based tracking. First objects are detected as blobs using codebook(CB) algorithm and scale invariant feature transform(SIFT) features are extracted from the blobs. Then vehicles are tracked by using SIFT to match the vehicles frame-by-frame...
Object detection and tracking has various application areas including intelligent transportation systems. We introduce an object detection and tracking approach that combines the background subtraction algorithm and the feature tracking and grouping algorithm. We first present an augmented background subtraction algorithm which uses a low-level feature tracking as a cue. The resulting background subtraction...
One of the core components of any visual surveillance system is object classification, where detected objects are classified into different categories of interest. Although in airports or train stations, abandoned objects are mainly luggage or trolleys, none of the existing works in the literature have attempted to classify or recognize trolleys. In this paper, we analyzed and classified images of...
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