Object Detection Device Using Shoulder Structure Height Estimation

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Solution Overview

Problem

Conventional image processing devices face difficulties in accurately distinguishing between objects and road surfaces when environment conditions are unsuitable for generating disparity information, leading to decreased position detection accuracy and potential erroneous object detection.

Innovation Solution

An object detection device equipped with a stereo camera, three-dimensional data generation unit, shoulder structure detection unit, structure ground-contact position derivation unit, road surface position estimation unit, and object detection unit, which calculates disparity data and estimates road surface height using ground-contact positions of shoulder structures to separate road surface and object disparity data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If disparity information is used to detect objects on the road surface, then object detection capability is improved, but detection accuracy decreases when the environment is unsuitable for generating disparity information

Engineering Contradiction:
Improveobject detection capabilityVSAvoidposition detection accuracy
Core Design Contradiction:
ReliabilityVSMeasurement precision

Solution Approach 1:

The patent introduces shoulder structures (guardrails, barriers, signs) as intermediary reference objects to estimate road surface height. These structures provide stable reference points that do not depend on disparity information quality, acting as mediators between the detection system and the road surface when disparity-based detection fails

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The system switches from using disparity information as the primary parameter for road surface detection to using height parameters derived from shoulder structure positions. This parameter change allows accurate road surface estimation in environments where disparity information is unreliable

Inventive Principle:
Principle #35Parameter changes

2Reliability

If conventional disparity-based detection is used, then object detection is possible, but confusion between road surface and object occurs leading to erroneous detection

Engineering Contradiction:
Improvedetection capabilityVSAvoiddetection accuracy
Core Design Contradiction:
ReliabilityVSMeasurement precision

Solution Approach 1:

The patent segments the detection space by first identifying shoulder structures and using them to define the road surface boundary. This segmentation separates the road surface detection task from general object detection, preventing confusion between the two by establishing clear spatial boundaries derived from shoulder structure positions

Inventive Principle:
Principle #1Segmentation

Data Source

PatentEP3557527B1Object detection device
Publication Date: 2024.06.19 ASTEMO LTD
  • EP3557527B1 patent drawingFigure 1(a)~2
  • EP3557527B1 patent drawingFigure 3
  • EP3557527B1 patent drawingFigure 4(a)~4(b)

AI summary

The purpose of the present invention is to provide an object detection device which is capable of accurately estimating the height of a road surface and is capable of reliably detecting an object present on the road surface. This object detection device 1 detects objects upon a road surface, and is equipped with: a stereo camera 110 for capturing images of the road surface 101a and the road shoulder 101b and generating image data; a three-dimensional data generation unit 210 for calculating disparity data for the pixels in the image data; a shoulder structure detection unit 310 for using the disparity data and/or the image data to detect shoulder structures; a structure ground-contact position derivation unit 410 for deriving the ground-contact position of a shoulder structure; a road surface position estimation unit 510 for estimating the height of the road surface 101a from the ground-contact position of the shoulder structure; and an object detection unit 610 for detecting an object 105 upon the road surface 101a by using the disparity data and the road surface height to separate disparity data corresponding to the road surface 101a and disparity data for the object.