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Detection of pedestrian crossing road is the objective of this work. The model incorporates the pedestrian pose recognition and lateral speed, motion direction and spatial layout of the environment. Pedestrian poses are recognized according to the spatial body language ratio. The center of mass of the body relative to its width and height is used to define the pedestrian pose. Motion trajectory is...
In the automatic video surveillance system, the detection of a human carrying baggage is a potentially important objective for security and monitoring purposes in the public spaces. This paper introduces a new approach for detecting and classifying baggage carried by a human on the images. It utilizes the spatial information of the baggage in reference to the body of the human carrying it. A human-baggage...
Foreground detection can be considered as backbone of multistage computer vision systems. Foreground detection using Gaussian Mixture Models (GMM) is famous choice because of its good accuracy and low computational cost. There are several parameters (e.g., learning rate, mean, and variance) involved in the model and assigning appropriate values may lead to better foreground segmentation. This paper...
This paper introduces a method for analyzing the critical situation based on collision risk probability. Pedestrians in the scene are captured from a monocular camera mounted on the vehicle. Position information of object is extracted by projecting the centroid of bounding box to the ground plane. Five elements of collision criteria are used for our risk analysis. Pedestrian walking direction, its...
The aim of this work is to improve driver awareness by proposing a collision risk analysis method. Pedestrian in the scene is observed by sequential frames from monocular camera mounted on the car. Positional information of object is extracted by projecting the centroid of bounding box on the ground plane. Four elements of collision criteria are constructed which are pedestrian walking direction,...
In this paper a road environment recognition method for intelligent vehicle systems is introduced. This is done in order to increase safety since road environment is a complex problem. We introduce the ongoing results of our obstacle classification based on sensor merging using camera and laser range finder sensors. Firstly, a laser-camera calibration is performed. Secondly, objects are extracted...
This paper proposes probabilistic foreground detector based on Gaussian Mixture Models (GMM) for sterile zone monitoring at night time. The foreground object may exhibit camouflage effect due to the thermal camera. GMM is prone to camouflage effect. The proposed system consists of three modules namely pre-processing, foreground detection, and post processing. Firstly, every frame is enhanced using...
Probabilistic modeling of background is extensively used for foreground detection in computer vision. Gaussian Mixture Models (GMM) is famous choice for detecting foreground in video sequences owing to ability of adapting background variation. However, GMM is prone to camouflage effect i.e. foreground object and background having same pixel intensity. This paper proposes foreground detector based...
This study explores a unique pose of human walking by proposing centroid based pose ratio for pedestrian action recognition. Our proposal uses width and height of bounding box, and also centroid of human shape to compute a pose ratio. Then, the proposed model incorporates the pose ratio with pedestrian lateral speed, walking direction and spatial layout of the environment to perform action classification...
A collision risk estimation plays a crucial role in both driver and pedestrian safety in advanced driver assistance systems (ADAS) and autonomous vehicle navigation(AVN). In the proposed approach, an object warning collision system is implemented using a laser sensor. We focus on high conflict vehicle/pedestrian zones within a range of [20km/h, 30km/h]. The proposed method was implemented in four...
This paper presents a method for estimating of walking direction for pedestrian path prediction. Pedestrian intending to laterally cross the street is observed by images which captured from a monocular camera mounted on the vehicle. The positional information of object is obtained by projecting the centroid of bounding box in the ground plane. Then, dependency between the real worlds, global coordinates...
Accurate pedestrian path prediction and motion estimation are important tasks in the intelligent vehicle domain. The model incorporates the pedestrian pose recognition and lateral speed, motion direction and spatial layout of the environment. Pedestrian poses are recognized according to the spatial body language ratio. The region of interest of detected human is used. Then the centroid of the body...
Detection of pedestrian crossing road is described in this paper. Single camera is used to detect pedestrians, thus classify them as a pedestrian crossing road or not. The moving pedestrian is detected using improved sparse optical flow method. The proposed technique consists of three main components. First, overlapping blocks are applied in consecutive images. KLT tracker is used to find corresponding...
This paper presents a detection of pedestrian crossing road method using action classification model. The model incorporates the pedestrian pose recognition, lateral speed and spatial layout of the environment. The spatial body language ratio is used for recognize the pedestrian pose. The center of mass of the body relative to its width and height is used to define the pedestrian pose. Motion trajectory...
Pedestrian motion type classification is proposed in this work. The model incorporates the pedestrian pose recognition and lateral speed, motion direction and spatial layout of the environment. Pedestrian poses are recognized according to the spatial body language ratio. The center of mass of the body relative to its width and height is used to define the pedestrian pose. Motion trajectory is obtained...
This paper presents a comparative study of several state of the art background subtraction (BS) algorithms. The goal is to provide brief solid overview of the strengths and weaknesses of the most widely applied BS methods. Approaches ranging from simple background subtraction with global thresholding to more sophisticated statistical methods have been implemented and tested with ground truth. The...
This paper proposes a method to detect pedestrians from a single camera mounted on the vehicle then classify the location of the pedestrian to give information for the driver assistance system. The system consists of three stages. First, moving objects are detected using optical flows method. A moving object is extracted from the relative motion by segmenting the region representing the same optical...
In past two decades, developing a system that can navigate vehicle autonomously becomes more interesting problem. The vehicle is equipped by sensors, such as radar, laser, GPS, and camera for sensing the surrounding. Among them, utilization of camera with computer vision technique is the most adopted method for constructing such a system. It is because camera provides a lot of information and is low-cost...
In automatic navigation of mobile systems, first, they require providing a path network for robot/vehicle motion. Therefore, path planning is an important task of autonomous vehicle systems. To deal with the problem, this paper presents a method for constructing the shortest path, which support for vehicle auto-navigation in outdoor environments. The method using online road map images to estimate...
This paper presents a technique to enhance accuracy of omnidirectional camera calibration which is applied structure from motion. We use two omnidirectional images of a predefined trihedron with checker board taken by a calibrate camera at an arbitrary location. Then, several point matches were picked manually from both views of the object. After that, compute and perform a 3D metric reconstruction...
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