[go: up one dir, main page]

MX2018000835A - Deteccion de vehiculos en condiciones de iluminacion baja. - Google Patents

Deteccion de vehiculos en condiciones de iluminacion baja.

Info

Publication number
MX2018000835A
MX2018000835A MX2018000835A MX2018000835A MX2018000835A MX 2018000835 A MX2018000835 A MX 2018000835A MX 2018000835 A MX2018000835 A MX 2018000835A MX 2018000835 A MX2018000835 A MX 2018000835A MX 2018000835 A MX2018000835 A MX 2018000835A
Authority
MX
Mexico
Prior art keywords
vehicles
contours
vehicle
low light
light conditions
Prior art date
Application number
MX2018000835A
Other languages
English (en)
Inventor
Nariyambut Murali Vidya
J Goh Madeline
Moosaei Maryam
Hotson Guy
Original Assignee
Ford Global Tech Llc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Ford Global Tech Llc filed Critical Ford Global Tech Llc
Publication of MX2018000835A publication Critical patent/MX2018000835A/es

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/86—Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
    • G06F18/24133—Distances to prototypes
    • G06F18/24137—Distances to cluster centroïds
    • G06F18/2414—Smoothing the distance, e.g. radial basis function networks [RBFN]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • G06V20/584—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of vehicle lights or traffic lights
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00—Television systems
    • H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
    • H04N7/183—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a single remote source
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/08—Detecting or categorising vehicles

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Evolutionary Computation (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Electromagnetism (AREA)
  • Health & Medical Sciences (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Software Systems (AREA)
  • General Health & Medical Sciences (AREA)
  • Databases & Information Systems (AREA)
  • Computing Systems (AREA)
  • Signal Processing (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Traffic Control Systems (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Business, Economics & Management (AREA)
  • Game Theory and Decision Science (AREA)
  • Mechanical Engineering (AREA)

Abstract

La presente invención abarca métodos, sistemas y programas informáticos para detectar vehículos en condiciones de iluminación baja. Se usan cámaras para obtener imágenes RGB del entorno alrededor de un vehículo. Las imágenes RGB se convierten en imágenes LAB. El canal ``A´´ se filtra para extraer contornos de las imágenes LAB. Los contornos se filtran basándose en sus formas/tamaños para reducir los falsos positivos a partir de los contornos que sea poco probable que correspondan a vehículos. Una red neuronal clasifica un objeto como un vehículo o no vehículo basándose en los contornos. Por consiguiente, los aspectos proporcionan una conducción autónoma confiable con sensores más económicos y con una mejor estética. Pueden detectarse vehículos en la noche, así como en otras condiciones de iluminación baja, mediante el uso de sus luces delanteras y luces traseras, lo cual permite que los vehículos autónomos detecten mejor otros vehículos en su entorno. Las detecciones de vehículos pueden facilitarse mediante el uso de una combinación de datos virtuales, aprendizaje profundo y visión informática.
MX2018000835A 2017-01-25 2018-01-19 Deteccion de vehiculos en condiciones de iluminacion baja. MX2018000835A (es)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
US15/415,733 US20180211121A1 (en) 2017-01-25 2017-01-25 Detecting Vehicles In Low Light Conditions

Publications (1)

Publication Number Publication Date
MX2018000835A true MX2018000835A (es) 2018-11-09

Family

ID=61283751

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2018000835A MX2018000835A (es) 2017-01-25 2018-01-19 Deteccion de vehiculos en condiciones de iluminacion baja.

Country Status (6)

Country Link
US (1) US20180211121A1 (es)
CN (1) CN108345840A (es)
DE (1) DE102018101366A1 (es)
GB (1) GB2560625A (es)
MX (1) MX2018000835A (es)
RU (1) RU2018102638A (es)

Families Citing this family (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10796204B2 (en) * 2017-02-27 2020-10-06 Huawei Technologies Co., Ltd. Planning system and method for controlling operation of an autonomous vehicle to navigate a planned path
CN109697458A (zh) * 2018-11-27 2019-04-30 深圳前海达闼云端智能科技有限公司 控制设备移动的方法、装置、存储介质及电子设备
CN112912896B (zh) * 2018-12-14 2024-06-28 苹果公司 机器学习辅助的图像预测
KR102751276B1 (ko) * 2019-06-07 2025-01-10 현대자동차주식회사 자율주행차량의 위치 인식 장치 및 그 방법
US12061971B2 (en) 2019-08-12 2024-08-13 Micron Technology, Inc. Predictive maintenance of automotive engines
US12249189B2 (en) * 2019-08-12 2025-03-11 Micron Technology, Inc. Predictive maintenance of automotive lighting
US11042350B2 (en) 2019-08-21 2021-06-22 Micron Technology, Inc. Intelligent audio control in vehicles
US12497055B2 (en) 2019-08-21 2025-12-16 Micron Technology, Inc. Monitoring controller area network bus for vehicle control
US12210401B2 (en) 2019-09-05 2025-01-28 Micron Technology, Inc. Temperature based optimization of data storage operations
EP3806065A1 (en) 2019-10-11 2021-04-14 Aptiv Technologies Limited Method and system for determining an attribute of an object at a pre-determined time point
CN110909666B (zh) * 2019-11-20 2022-10-25 西安交通大学 一种基于改进型YOLOv3卷积神经网络的夜间车辆检测方法
US11250648B2 (en) 2019-12-18 2022-02-15 Micron Technology, Inc. Predictive maintenance of automotive transmission
US11823458B2 (en) 2020-06-18 2023-11-21 Embedtek, LLC Object detection and tracking system
US11568688B2 (en) * 2020-08-25 2023-01-31 Motional Ad Llc Simulation of autonomous vehicle to improve safety and reliability of autonomous vehicle
CN112308803B (zh) * 2020-11-25 2021-10-01 哈尔滨工业大学 一种基于深度学习的自监督低照度图像增强及去噪方法
EP4113460A1 (en) * 2021-06-29 2023-01-04 Ford Global Technologies, LLC Driver assistance system and method improving its situational awareness
JP7537027B2 (ja) * 2021-07-26 2024-08-20 京セラ株式会社 学習済みモデル生成方法、学習済みモデル生成装置、及び学習済みモデル生成システム
US11766938B1 (en) * 2022-03-23 2023-09-26 GM Global Technology Operations LLC Augmented reality head-up display for overlaying a notification symbol over a visually imperceptible object
WO2023194826A1 (en) * 2022-04-04 2023-10-12 3M Innovative Properties Company Thermal imaging with ai image identification
WO2024146446A1 (en) * 2023-01-04 2024-07-11 Douyin Vision Co., Ltd. Method, apparatus, and medium for video processing
CN117523526B (zh) * 2023-11-02 2024-07-30 深圳鑫扬明科技有限公司 一种基于机器视觉的车辆检测系统及方法
CN117459669B (zh) * 2023-11-14 2024-06-14 镁佳(武汉)科技有限公司 一种基于虚拟摄像头的视觉应用开发方法及系统

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5487116A (en) * 1993-05-25 1996-01-23 Matsushita Electric Industrial Co., Ltd. Vehicle recognition apparatus
US9122934B2 (en) * 2013-12-27 2015-09-01 Automotive Research & Testing Center Object detection method with a rising classifier effect and object detection device with the same
CN105313782B (zh) * 2014-07-28 2018-01-23 现代摩比斯株式会社 车辆行驶辅助系统及其方法

Also Published As

Publication number Publication date
US20180211121A1 (en) 2018-07-26
CN108345840A (zh) 2018-07-31
GB2560625A (en) 2018-09-19
RU2018102638A (ru) 2019-07-25
GB201801029D0 (en) 2018-03-07
DE102018101366A1 (de) 2018-07-26

Similar Documents

Publication Publication Date Title
MX2018000835A (es) Deteccion de vehiculos en condiciones de iluminacion baja.
US11386673B2 (en) Brake light detection
US10509961B2 (en) Blindman navigation method and blindman navigation apparatus
CN108090411B (zh) 使用计算机视觉和深度学习进行交通信号灯检测和分类
MX2017014636A (es) Deteccion y respuesta a vehiculos de emergencia en una carretera.
CN106169244B (zh) 利用人行横道识别结果的引导信息提供装置及方法
EP3506169B1 (en) Driver assistance system and method for object detection and notification
MX2017004705A (es) Deteccion de lluvia basada en vision con aprendizaje profundo.
CN108357418B (zh) 一种基于尾灯识别的前车驾驶意图分析方法
CN105678212B (zh) 隧道判定方法和装置
MX369189B (es) Dispositivo de entendimiento de escena.
WO2018047114A3 (en) Automated situation dependent decision making in vehicle based on an annotated environmental model
EP3851351A3 (en) A robust method for detecting traffic signals and their associated states
MY158374A (en) Three-dimensional object detection device and three-dimensional object detection method
KR102277018B1 (ko) 차량 주행 보조 장치 및 차량 주행 보조 방법
MY182981A (en) Travel control method and travel control apparatus
CN104442566A (zh) 一种车内乘员危险状态报警装置及报警方法
CN205256314U (zh) 自动驾驶汽车中应用机器视觉自动识别交通信号灯的装置
CN105530404A (zh) 影像识别装置及影像识别方法
US20230368545A1 (en) Method for processing images
US9127941B2 (en) System for measuring vehicle distance and method thereof
MX2017014885A (es) Deteccion de motocicletas divisoras de carril.
KR101616462B1 (ko) 차량의 브레이크등을 이용한 야간 전방 차량 인식 방법 및 시스템
CN107512215A (zh) 一种汽车灯光自动启闭系统
Moon et al. Robust visual detection of brake-lights in front for commercialized dashboard camera