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Pedestrian detection is one of the most challenging and vital tasks of driver assistance systems (DAS). Among several algorithms developed for human detection, histogram of oriented gradients (HOG) followed by support vector machine (SVM) has shown the most promising results. This paper presents a hardware accelerator for real-time pedestrian detection at different scales to fulfill the real-time...
We introduce a new computer vision based system for robust traffic sign recognition and tracking. Such a system presents a vital support for driver assistance in an intelligent automotive. Firstly, a color based segmentation method is applied to generate traffic sign candidate regions. Secondly, the HoG features are extracted to encode the detected traffic signs and then generating the feature vector...
Traffic signs serve important functions on the road. Drivers can easily determine their directions and vehicle speeds by paying attention to traffic signs. However, it is only natural that sometimes drivers misjudge the position and meaning of traffic signs that they ignore them and in the worst case scenario, got involved in accidents. Therefore, technological improvements allow the development of...
Automation techniques have been applied in almost every field in past few years. Automated Guided Vehicle (AGV) are most often used in industries and inventories for object management. Obstacle avoidance being a necessary requirement for navigation in any vehicle, still faces many challenges in the field of automation due to uncertain nature of the surrounding environment. This paper presents the...
The proposed system comes in the context of intelligent parking lots management and presents an approach for vacant parking spots detection and localization. Our system provides a camera-based solution, which can deal with outdoor parking lots. It returns the real time states of the parking lots providing the number of available vacant places and its specific positions in order to guide the drivers...
Traditional vehicle recognition and retrieval systems are almost based on vehicle license plate recognition, which requires the user to provide images containing the license plate of the vehicle. In order to recognize and retrieve vehicles more convenient and efficient, and solve the problem of missing or wrong license plate, this paper proposes a method based on the overall appearance characteristics...
This paper intends to investigate stress level detection of a driver during real world driving experiment. This detection is based on heart rate variability (HRV) analysis which is derived from ECG signal and reflects autonomic nervous system state of the human body. The alteration of autonomic nervous system predicts the stress level of drivers during driving operation and permits a safe driving...
Support Vector Machine (SVM) classifier with Histogram of Oriented Gradients (HOG) feature become one of the most popular techniques used for vehicle detection in recent years. And the computing time of SVM is a main obstacle to get real time implementation which is important for Advanced Driver Assistance Systems (ADAS) applications. One of the effective ways to reduce the computing complexity of...
This paper presents a fast vehicle recognition and vehicle retrieval system based on “bag of words”. In this system, the input is an image of vehicle and the vehicle will be identified automatically, it can also retrieve images which are similar to the input image. 3742 vehicle images which include 28 types of vehicles are collected as the image database. Features of these images are extracted and...
The proper identification of the traffic signs can ensure driving safety and can play a very important role in reducing the number of road accidents significantly. This paper represents a uniform way to detect the speed limit traffic signs and to confirm it by recognizing the sign's speed number. In this system, firstly the red color objects are segmented from an image using LVQ. Secondly, detected...
Drowsiness is one of the main causes of severe traffic accidents occurring in our daily life. In order to reduce the number of drowsiness-induced accidents, various researches have been conducted with the aim of finding practical and non-invasive drowsiness detection systems by using behavioral measuring techniques. Many of the previous works on behavioral measuring techniques have mainly focused...
Intelligent Transportation System is a worldwide research hotspot and the extraction of traffic parameters is a crucial part of it for subsequent identification of traffic states. This paper proposes a novel approach of extracting traffic parameters such as time occupancy, volume and vehicle velocity based on video images. Visual features obtained from spatio-temporal images are more immune to environmental...
Vehicle Detection is an important part in intelligent transportation system (ITS) and driver assistance system. Considering vehicles have strong edges and lines in different orientation and scales, in this paper, we presents a method for detecting vehicles based on a feature named Pyramid Histogram of Oriented Gradient. This feature provides spatial distribution information of edges which was often...
Due to the increment of vehicles, the traffic jamming in cities becomes a serious challenge and the safety of people is threatened. Intelligent transportation system (ITS) and intelligent vehicles are critical to the efficiency of city transportation. In the area related with ITS and intelligent vehicles, moving vehicle detection and tracking are the most challenging problems. In this paper, we propose...
This paper presents a vision-based real-time vehicle detection approach. Combining segmenting the specific shadow area underneath the vehicle and using SVM-based classifier, the proposed approach is accurate and efficient for intelLigent vehicle. Experiment results with test dataset from real traffic scenes on freeways and urban roads are presented to illustrate the performance of this approach.
Road detection is an important problem with application to driver assistance systems and autonomous, self-guided vehicles. The focus of this paper is on the problem of feature extraction and classification for front-view road detection. Specifically, we propose using Support Vector Machines (SVM) for road detection and effective approach for self-supervised online learning. The proposed road detection...
Vital problems in transportation such as mobility and safety of transportation, especially in highways and road ways, are considered as very important nowadays. Road traffic monitoring aims at acquisition and analysis of traffic signs, such as presence and numbers of vehicles, and automatic driver warning systems developed mainly for localization and safety purposes. In the past some methods have...
There are important significance and social benefit of the application for real-time classification by using of the combination of GA, PCA and Improved SVM in a road ramp. The eight test points were put on the both sides of the road ramp, extracted feature vectors. The acoustic and seismic signals were used to research the classification in real-time. Because the dimension of feature vectors is too...
There is an important significance of the application for real-time classification by using of the acoustic and seismic signals generated by vehicles in the road ramp. The eight test points were put on the both sides of a road ramp, the some devices of acoustic and seismic sensors etc were put in each point. On the acquisition of acoustic and seismic signals, short-time Fourier transform (STFT) was...
An approach of power spectrum estimation is utilized to extract the feature vectors from acoustic signal radiated from different types of moving vehicles. A method of feature selection based on principal component analysis (PCA) is proposed to reconstruct effective feature vectors via dimension reduction. The classification of three typical targets is achieved by supported vector machine (SVM). Experiment...
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