Rearlamp Vehicle Detection And Tracking In Lowexposure Color Video For Night Conditions

• doi: 10.1109/TITS.2010.2045375
• title: Rear-Lamp Vehicle Detection and Tracking in Low-Exposure Color Video for Night Conditions
• publisher: IEEE
• isbn:
• issn: 1558-0016
• rank: 3420
• access_type: LOCKED
• content_type: Journals
• abstract: Automated detection of vehicles in front is an integral component of many advanced driver-assistance systems (ADAS), such as collision mitigation, automatic cruise control (ACC), and automatic headlamp dimming. We present a novel image processing system to detect and track vehicle rear-lamp pairs in forward-facing color video. A standard low-cost camera with a complementary metal-oxide semiconductor (CMOS) sensor and Bayer red-green-blue (RGB) color filter is used and could be utilized for full-color image display or other color image processing applications. The appearance of rear lamps in video and imagery can dramatically change, depending on camera hardware; therefore, we suggest a camera-configuration process that optimizes the appearance of rear lamps for segmentation. Rear-facing lamps are segmented from low-exposure forward-facing color video using a red-color threshold. Unlike previous work in the area, which uses subjective color threshold boundaries, our color threshold is directly derived from automotive regulations and adapted for real-world conditions in the hue-saturation-value (HSV) color space. Lamps are paired using color cross-correlation symmetry analysis and tracked using Kalman filtering. A tracking-based detection stage is introduced to improve robustness and to deal with distortions caused by other light sources and perspective distortion, which are common in automotive environments. Results that demonstrate the system's high detection rates, operating distance, and robustness to different lighting conditions and road environments are presented.
• article_number: 5446402
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5446402
• html_url: https://ieeexplore.ieee.org/document/5446402/
• abstract_url: https://ieeexplore.ieee.org/document/5446402/
• publication_title: IEEE Transactions on Intelligent Transportation Systems
• conference_location:
• conference_dates:
• publication_number: 6979
• is_number: 5475419
• publication_year: 2010
• publication_date: June 2010
• start_page: 453
• end_page: 462
• citing_paper_count: 186
• citing_patent_count: 5
• download_count: 4483
• insert_date: 20100412
• index_terms:
  • ieee_terms:
    • Vehicle detection
    • Color
    • Lamps
    • CMOS image sensors
    • Cameras
    • Image segmentation
    • Automotive engineering
    • Robustness
    • Vehicle driving
    • Collision mitigation
  • author_terms:
    • Computer vision
    • driver assistance
    • tail-lamp detection
    • vehicle detection
    • video processing
  • dynamic_index_terms:
    • Vehicle Detection
    • Color Video
    • Distortion
    • Image Processing
    • Light Source
    • Cross-correlation
    • Color Images
    • Kalman Filter
    • Automatic Control
    • Color Space
    • Color Components
    • Higher Detection Rate
    • Headlights
    • Headlamp
    • Advanced Driver Assistance Systems
    • Driver Assistance Systems
    • Color Threshold
    • Front Vehicle
    • Perspective Distortion
    • Pairing
    • Light Intensity
    • Redness
    • Red S
    • Target Vehicle
    • Color Information
    • Low Exposure
    • Successful Detection
    • Standard Light
    • Street Lighting
    • Daylight Conditions
    • Ambient Light Conditions
    • High Dynamic Range
    • Bounding Box
    • Automatic Exposure Control
• authors:
  • Author Name: Ronan O'Malley
    Affiliation: Connaught Automotive Research Group, Electrical and Electronic Engineering, National University of Ireland, Galway, Ireland
    Author URL: https://ieeexplore.ieee.org/author/37398448900
    ID: 37398448900
    Order: 1
    Author Affiliations:
    • Connaught Automotive Research Group, Electrical and Electronic Engineering, National University of Ireland, Galway, Ireland
  • Author Name: Edward Jones
    Affiliation: Connaught Automotive Research Group, Electrical and Electronic Engineering, National University of Ireland, Galway, Ireland
    Author URL: https://ieeexplore.ieee.org/author/37266601500
    ID: 37266601500
    Order: 2
    Author Affiliations:
    • Connaught Automotive Research Group, Electrical and Electronic Engineering, National University of Ireland, Galway, Ireland
  • Author Name: Martin Glavin
    Affiliation: Connaught Automotive Research Group, Electrical and Electronic Engineering, National University of Ireland, Galway, Ireland
    Author URL: https://ieeexplore.ieee.org/author/37266602400
    ID: 37266602400
    Order: 3
    Author Affiliations:
    • Connaught Automotive Research Group, Electrical and Electronic Engineering, National University of Ireland, Galway, Ireland

Image Sensor

• sensor_type: CMOS
• resolution: 720x576
• dynamic_range: To be extracted from paper
• pixel_size: To be extracted from paper
• dark_current: To be extracted from paper

Optical Data

• focal_length: To be extracted from paper
• aperture: To be extracted from paper
• field_of_view: To be extracted from paper
• distortion: To be extracted from paper

Performance Metrics

• frame_rate: 25 Hz
• signal_to_noise_ratio: To be extracted from paper
• sensitivity: To be extracted from paper
• shutter_speed: To be extracted from paper
• power_consumption: To be extracted from paper
• noise: To be extracted from paper

Applications & Benefits

• cell_imaging: Not specifically mentioned in the paper, but CMOS technology is generally applicable.
• benefits: Low-cost, readily available for automotive systems.

Supporting Organizations

• supported_by: Irish Research Council for Science, Engineering and Technology Embark Initiative

Manuscript Details

• publication_date: June 2010

Relevancy Score

• score: 10
• missing_fields:
  • dynamic_range
  • pixel_size
  • dark_current
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • signal_to_noise_ratio
  • sensitivity
  • shutter_speed
  • power_consumption
  • noise

Processed JSON Filename

request_027a5016-dc65-4b15-af06-fe082962fdc4-rearlamp_vehicle_detection_and_tracking_in_lowexposure_color_video_for_night_conditions.json