Autonomous Driving Object Detection via Shadow and Reflection Analysis

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Solution Overview

Problem

Conventional autonomous driving systems often overlook shadows and reflections, which can provide valuable information about objects not directly visible in the scene, leading to incomplete scene understanding and potentially compromised safety.

Innovation Solution

The system utilizes shadow and reflection detection technologies, including ray tracing and shadow map techniques, to analyze electronic images and reconstruct information about occluding objects, thereby enhancing object detection and tracking for improved autonomous vehicle guidance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If conventional object detection systems only analyze directly visible objects, then the system complexity remains low, but the scene understanding completeness deteriorates

Engineering Contradiction:
Improvescene understanding completenessVSAvoiddetection system complexity
Core Design Contradiction:
Loss of informationVSDevice complexity

Solution Approach 1:

The patent uses shadows and reflections as intermediary elements to indirectly detect occluded objects. Instead of directly observing hidden objects, the system analyzes the shadows they cast and their reflections in surfaces, thereby recovering information about objects that would otherwise be invisible to the detection system.

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces direct optical detection with indirect detection methods using computational analysis of shadows and reflections. Rather than relying on direct line-of-sight optical paths, the system uses image processing algorithms to analyze light interaction patterns (shadows on surfaces, reflections in mirrors/water) to infer the presence and properties of occluded objects.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If the system incorporates shadow and reflection analysis, then object detection accuracy improves, but processing time increases

Engineering Contradiction:
Improveobject detection accuracyVSAvoidprocessing time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent segments the image processing task into distinct modules: direct object detection, shadow detection and analysis, reflection detection and analysis, and integration of results. This segmentation allows parallel processing of different detection streams and optimizes computational resources for each specific task, reducing overall processing time while maintaining comprehensive analysis.

Inventive Principle:
Principle #1Segmentation

3Reliability

If indirect information from shadows and reflections is utilized, then collision avoidance reliability improves, but computational requirements increase

Engineering Contradiction:
Improvecollision avoidance reliabilityVSAvoidcomputational power
Core Design Contradiction:
ReliabilityVSPower

Solution Approach 1:

The patent implements partial analysis by focusing computational resources on detecting and analyzing only the most informative shadows and reflections - those that provide critical information about occluded objects relevant to collision avoidance. Rather than analyzing every shadow and reflection in the scene, the system selectively processes those that contribute most to safety-critical decisions.

Inventive Principle:
Principle #16Partial or excessive action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach provides additional scene information, enabling better object detection and collision avoidance by incorporating indirect data from shadows and reflections, leading to more reliable and accurate autonomous driving decisions.

Implementation Method 1

The system utilizes shadow and reflection detection technologies, including ray tracing and shadow map techniques, to analyze electronic images and reconstruct information about occluding objects

Methodology Applied
Scientific EffectRay tracing:

Implementation Method 2

Conventional autonomous driving systems often overlook shadows and reflections, which can provide valuable information about objects not directly visible in the scene

Methodology Applied
Scientific EffectShadow formation: Shadow

Implementation Method 3

The system utilizes shadow and reflection detection technologies, including ray tracing and shadow map techniques, to analyze electronic images and reconstruct information about occluding objects

Methodology Applied
Scientific EffectReflection: Reflection

Data Source

PatentUS12033333B2Object detection and tracking for autonomous driving utilizing shadows and reflections
Publication Date: 2024.07.09 INTEL CORP
  • US12033333B2 patent drawing
  • US12033333B2 patent drawing
  • US12033333B2 patent drawing

AI summary

An embodiment of a semiconductor package apparatus may include technology to analyze an electronic image to determine indirect information including one or more of shadow information and reflection information, and provide the indirect information to a vehicle guidance system. Other embodiments are disclosed and claimed.