Road detection by using video




Compressed-domain object detection for video understanding
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1. The use of the proposed algorithm is demonstrated in the context of road detection . The detection of the road area is an important step towards detecting moving objects of in- terest in any road sequence (eg racing sequences, surveil- lance using moving cameras Most of the road boundary detection algorithms can be divided into two categories: feature-based and model-base methods. The feature-based methods locate the road areas using segmentation methods whereas the model-based methods represent the lane

Road detection using similarity search
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Fig. 1. Illustration of the road detection algorithm represents non- road then we can compute final likelihoods pi R The first and the second videos (called walk-01 and walk-02) were recorded using Canon XM2 camcorder on an autumn day with an overcast weather

Self-supervised monocular road detection in desert terrain.
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It can be seen that the road detection range is in this case about 70m, as opposed to only Our basic model of the road appearance is a mixture of Gaussians (MOG)-model in RGB space Our method is to classify all pixels in the training area using k-means clustering[16], and

Method for automated assessment of potholes, cracks and patches from road surface video clips
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subjected to various image processing techniques, supported by user defined decision logic for accurate detection of road surface distresses. The main steps in this algorithm are the segmentation of distress pixels from the background pixels of a video frame using an adaptive

Markov random fields (MRF)-based texture segmentation for road detection
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Traffic observation from airplane platforms using digital cameras is a fairly new application of Video Image Detection Systems (VIDS) In order to concentrate on road image processing algorithms were applied to distinguish between urban and surrounding vegetation areas

Traffic Lights Detection in Adverse Conditions using Color, Symmetry and Spatiotemporal Information.
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The problem of TLD in day and night scenes has been addressed by (Chunhe Yu et al.) using RGB thresholding and shape dimensions to detect and This paper presents a TLD algorithm inspired by the approaches followed for road sign detection , by (Barnes and

Performance evaluation of road detection and following algorithms
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frame of the analyzed video sequence, using the first variant of the algorithm. The three curves describe the false positive and false negative classification rate as well as the sum of both. The first frames illustrate a characteristic of the applied road detection algorithm, namely a

Proposed Method For Road Detection and Following Boundaries
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First the histogram of the whole image and road frame are calculated [17] models the contextual information shared between lane marker with the surroundings are modeled using a pixel hierarchy feature descriptor. Here lane detection is done using a learning-based approach

Bdd100k: A diverse driving video database with scalable annotation tooling
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In order for a vehicle perception system to be robust, it needs to learn from a variety of road condi- tions from numerous feature of our tool, sugges- tions on the category of a bounding box can be provided to annotators by using the outputs from an object detection model

Video based lane departure warning system using Hough transform
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image processing. This paper describes implementation of a lane detection system using Hough Transform. The proposed system can detect road lane markers in a video stream and an unintended departure from the lane. The

A traffic-flow parameters evaluation approach based on urban road video
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Step6: Error correction and accumulate total number; Figure6 shows the flowchart of vehicles counting algorithm using time-spatial image. Figure6. Flow chat for urban road vehicle counting method based on time-spatial image Canny edge detection Image preprocessing

Traffic surveillance system for vehicle detection using discrete wavelet transform
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Video sequences Nv Td Mv Fd Accuracy In this paper, an effective low-cost real time vehicle detection system is described using a stationary camera for traffic In addition, after road detection , all motion out of the interest zone will be ignored and the processing time will be

Adaptive Road Following using Self-Supervised Learning and Reverse Optical Flow.
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III. RESULTS A. Test Data Road detection by one-dimensional template matching using reverse optical flow worked well in a variety of test conditions. Single frame results from three different 720 x 480 pixel video sequences taken in the Mojave Desert are shown in Fig In our experiment, we generated datasets of flooded roads from ordinary road images, in sunny or rainy weather. Using augmented datasets, the detection accuracy of flooded, sunny, and rainy roads is compared to previous techniques to show the effectiveness of the

Automated video analysis as a tool for analysing road user behaviour
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For readability reasons we avoid using mathematical formulas in the text but refer instead to the special literature where ROAD USER DETECTION AND TRACKING A classical solution for detection and tracking objects in a video sequence is to use foreground/background

Automated safety analysis using video sensors: technology and case studies
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and for all of their static and dynamic conflict indicators, calculate the corresponding severity index 𝐼 using one of 8 Figure 1 Layout of the pedestrian detection and tracking system from low-level video data to a position database of detected, tracked, and classified road users In Fig. the video frames have been edited to demonstrate the concept. In addition, by using problem-specific feature sets we can further enhance accuracy. TAAWUN is a decision fusion and feature Specific road detection method for connected autonomous vehicles video are preprocessed by Pulse Coupled Neural Network (PCNN), and then handled by Kalman filter and Expectation Maximization (EM) algorithms. Next, according to the roads dif- ferent feathers, using fuzzy algorithm chooses a corresponding SVM for further lane detection

Review of on- road driver fatigue monitoring devices
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Uses twin video cameras and feature detection to estimate head pose and fast tracking recovery to cope with temporary loss of the face, low light Validated in simulator studies, evaluated using the Perclos methodology Review of on- road driver fatigue monitoring devices 8

Challenges in time-stamp aware anomaly detection in traffic videos
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Y. Xu, X. Ouyang, Y. Cheng, S. Yu, L. Xiong, C. Ng, S. Pranata, S. Shen, and J. Xing. Dual-mode vehicle motion pattern learning for high performance road traffic anomaly detection Abnormal event detection for video surveillance using deep one-class learning

Eye gaze tracking and eyes off the road detection for traffic safety on raspberry pi
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155 processing and can be passive image based or video feed based [10 The Haar Classifiers algorithm rapidly detects object using AdaBoost classifier cascades with help of Haar features [4 F. Eyes off the road detection and fatigue detection Similar to concept used in [9

A public video dataset for road transportation applications
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a lack of agreed standards for tracking and higher semantic interpretation such as event detection Road Users A typical use of video data for transportation is road user tracking The performance is computed using the PDTV tool for ground truth comparison presented previously

Deriving textual descriptions of road traffic queues from video sequences
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the sequel have been obtained with an older version of the vehicle detection and tracking originally used the rotational velocity about an axis normal to both the road plane and 17] NA Rota and M. Thonnat: Activity Recognition from Video Se- quences Using Declarative Models

Real-time road signs recognition using mobile GPU
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Abstract This article shows an effective implementation of the algorithm for detection of road signs using video obtained by a camera installed in a vehicle Paper presents an algorithm for the detection of road signs in video sequences using the current vehicle speed

Road tracking from UAV imagery using gradient information
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Hailing Zhou, Hui Kong, Lei Wei, Douglas Creighton, and Saeid Nahavandi. Efficient Road Detection and Tracking for Unmanned Aerial Vehicle J. Candamo, R. Kasturi, D. Goldgof. Using Color Profiles for Street Detection in Low-Altitude UAV Video . Proc

Land Cover Boundary Extraction in Rural Aerial Videos .
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A hybrid solution combining the results of a robust line detection and a colour-texture various land cover boundaries in rural aerial video and has been tested using 100 aerial Jackson, M. Mo- rimoto, S. Rathinam, J. Padial, and R. Sengupta, Vision-based Road Following Using

Detecting roads in stabilized video with the spatio-temporal structure tensor
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Figure 4 shows the effect of using progressively more frames of video . For densely travelled urban scenes, even 4 frames of video is sufficient to detect consistent hundreds of frames, other image variation (largely due to clouds) decreases the road detection score because the

Robust lane markings detection and road geometry computation
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Third, we quantitatively assess the method using four geometrically meaningful quantities derived from the They lack the in-depth quantitative performance evaluation of lane detection on synthetic results on fourteen long video sequences recorded on several road types and

Unsupervised Traffic Anomaly Detection Using Trajectories.
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than 0.7. SOT tracker is used to track 10 frames for each detection , and both results are processed using NMS with a threshold of 0.3. Then in 90. When judging whether the track is on the road , the threshold Tf is set to 0.9. Then

Video -Rate Image Processing System for an Autonomous Personal Vehicle System.
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It detects white lines on a road including straight sections, curves, and intersections, and detects obstacles in the road by using binocular 3D We developed white-line and obstacle detection algorithms that can be processed by the Fujitsu Integrated Visual Information System

Video based road traffic detection and analysis
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It contains data for statistical analysis of road traffic Prepared video was then analyzed by an application using different settings of the Motion Detection Filter This stage was intended to check the performance of vehicle detection algorithm and its sensitivity for parameters change

A prototype system for truck signal priority (tksp) using video sensors
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IEEE. [SS07] N. Saunier and T. Sayed. Automated Road Safety Analysis Using Video Data [SS08] N. Saunier and T. Sayed. A Probabilistic Framework for the Automated Analysis of the Exposure to Road Collision Rapid object detection using a boosted cascade of simple 12

On-board lane detection system for intelligent vehicle based on monocular vision.
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June 200 pp. 318-321. [17] Dahlkamp H, Kaehler A, Stavens D, Thrun S, Bradski G. Self-supervised monocular road detection in desert terrain pp.19-17. [19] Y Wang, EK Teoh, D Shen. Lane detection and tracking using B-snake . Image Visual Compute, 200 Vol

Road plane detection using differential homography estimated by pair feature matching of local regions
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consecutive video frames; the regions that satisfy the estimated differential homography are classified as road plane. The proposed algorithm is described in the following section, and the experimental results are shown in Section 3. 2 Road Plane Detection using Differential

Automated pedestrian safety analysis using video data in the context of scramble phase intersections
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An accurate estimation of TTC using field observations is prohibitive, requiring considerable field measurement The values of conflict indicators used in event detection are the minimum TTC, the video data to a position database of detected, tracked, and classified road users [32

Detection and Classification of Signages from Random Mobile Videos Using Local Binary Patterns
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13 mega pixel mobile camera mounted on bikes head in a systematic manner using self-stick This mechanism facilitates in acquiring real-time video stream of road signages so that the To make the data suitable for automatic detection of ROI and classification it is necessary to

A 2D image motion detection method using a stationary camera
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For the specific application of road traffic monitoring, where real time is mandatory and a static camera is used, there are 2. THE 2D MOTION DETECTION METHOD Since the objective of this method is real-time 2D motion detection on image sequences using low cost

Moving object tracking of vehicle detection : A concise review
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subtraction technique used to detect and extract features for vehicles in complex road scenes in A. Aggarwal, S. Biswas, S. Singh, S. Sural and AK Majundar, Object tracking using background subtraction Z. Duan, Z. Cain and J. Yu, Occlusion detection and recovery in

Video -based Road Detection Using Evolving GMMs and Region Enhancement
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In this article we propose a new online method for road detection which uses as input video captured by a single video camera. Our method consists of two stages. In the first stage we build a statistical road model using training data and in the second we detect the road area