[go: up one dir, main page]

Berriel et al., 2017 - Google Patents

Ego-lane analysis system (elas): Dataset and algorithms

Berriel et al., 2017

View PDF
Document ID
5558237511249839856
Author
Berriel R
de Aguiar E
De Souza A
Oliveira-Santos T
Publication year
Publication venue
Image and Vision Computing

External Links

Snippet

Decreasing costs of vision sensors and advances in embedded hardware boosted lane related research–detection, estimation, tracking, etc.–in the past two decades. The interest in this topic has increased even more with the demand for advanced driver assistance systems …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • G06K9/00798—Recognition of lanes or road borders, e.g. of lane markings, or recognition of driver's driving pattern in relation to lanes perceived from the vehicle; Analysis of car trajectory relative to detected road
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • G06K9/00805—Detecting potential obstacles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • G06K9/00818—Recognising traffic signs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/20—Image acquisition
    • G06K9/32—Aligning or centering of the image pick-up or image-field
    • G06K9/3233—Determination of region of interest
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30248—Vehicle exterior or interior
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors

Similar Documents

Publication Publication Date Title
Berriel et al. Ego-lane analysis system (elas): Dataset and algorithms
Song et al. Lane detection and classification for forward collision warning system based on stereo vision
Kastrinaki et al. A survey of video processing techniques for traffic applications
US8670592B2 (en) Clear path detection using segmentation-based method
Borkar et al. A layered approach to robust lane detection at night
Kuo et al. Vision-based vehicle detection for a driver assistance system
US8611585B2 (en) Clear path detection using patch approach
KR101191308B1 (en) Road and lane detection system for intelligent transportation system and method therefor
Samadzadegan et al. Automatic lane detection in image sequences for vision-based navigation purposes
Berriel et al. A particle filter-based lane marker tracking approach using a cubic spline model
Poggenhans et al. A universal approach to detect and classify road surface markings
Qing et al. A novel particle filter implementation for a multiple-vehicle detection and tracking system using tail light segmentation
Wu et al. A Real‐Time Embedded Blind Spot Safety Assistance System
Kim et al. An intelligent and integrated driver assistance system for increased safety and convenience based on all-around sensing
Xiong et al. Fast and robust approaches for lane detection using multi‐camera fusion in complex scenes
Kanhere Vision-based detection, tracking and classification of vehicles using stable features with automatic camera calibration
Zaidi et al. Lane detection in autonomous driving: a comprehensive survey of methods and performance
Bhupathi et al. Sharp Curve Detection of Autonomous Vehicles using DBSCAN and Augmented Sliding Window Techniques
Xuan et al. Robust lane-mark extraction for autonomous driving under complex real conditions
Dai et al. A driving assistance system with vision based vehicle detection techniques
Ng et al. Real-time detection of objects on roads for autonomous vehicles using deep learning
Wen et al. Road boundary detection in complex urban environment based on low-resolution vision
Kumar Vehicle detection in monocular night-time grey-level videos
Kim et al. Robust lane detection for video-based navigation systems
Yu et al. An efficient extraction of on-road object and lane information using representation method