English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Detectability Prediction for Increased Scene Awareness

Engel, D., & Curio, C. (2013). Detectability Prediction for Increased Scene Awareness. IEEE Intelligent Transportation Systems Magazine, 5(4), 146-157. doi:10.1109/MITS.2013.2272473.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-001A-12EA-D Version Permalink: http://hdl.handle.net/21.11116/0000-0003-1872-2
Genre: Journal Article

Files

show Files

Locators

show
hide
Description:
-

Creators

show
hide
 Creators:
Engel, D, Author              
Curio, C1, 2, 3, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              
3Project group: Cognitive Engineering, Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_2528702              

Content

show
hide
Free keywords: -
 Abstract: A driver assistance system realizes that the driver is distracted and that a potentially hazardous situation is emerging. In this scenario the driver needs to make an optimal decision as fast as possible. His attention needs to be directed to the location that enhances the perception of all action relevant entities. But where is that optimal spot? Pedestrian detectability is a measure of the probability that a driver perceives pedestrians in static and dynamic scenes. Leveraging this information allows a driver assistance system to direct the attention of the driver to the spot that maximizes the probability that all pedestrians are seen.

Details

show
hide
Language(s):
 Dates: 2013-10
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1109/MITS.2013.2272473
BibTex Citekey: EngelC2013
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: IEEE Intelligent Transportation Systems Magazine
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 5 (4) Sequence Number: - Start / End Page: 146 - 157 Identifier: -