Vehicle Motion Vector Correlation for In-Car Object Detection
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Solution Overview
Problem
Existing camera systems installed in vehicles struggle to accurately distinguish between in-vehicle and out-of-vehicle regions in video data, leading to difficulties in identifying moving objects within the vehicle.
Innovation Solution
A control apparatus equipped with an acceleration detection unit, processor, and memory that determines motion vectors from video data within a vehicle, correlating the change in motion vectors with vehicle acceleration to identify out-of-vehicle regions and exclude them, thereby isolating in-vehicle moving objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If motion vectors from video data are analyzed to identify moving objects, then object detection capability is improved, but accuracy in distinguishing in-vehicle from out-of-vehicle regions deteriorates
Solution Approach 1:
The patent introduces acceleration information as an intermediary parameter to mediate between motion vectors and region classification. By correlating motion vector changes with acceleration data, the system can distinguish whether observed motion is due to vehicle movement or actual object movement within the vehicle, thereby resolving the ambiguity in region classification
Solution Approach 2:
The patent changes the parameter set used for analysis by incorporating acceleration data alongside motion vectors. This multi-parameter approach allows the system to differentiate between global vehicle motion and local object motion, improving the accuracy of in-vehicle versus out-of-vehicle region distinction
2Productivity
If all motion vectors in video data are used for analysis, then comprehensive object detection is improved, but computational complexity increases
Solution Approach 1:
The patent extracts and isolates motion vectors that are correlated with acceleration patterns, separating them from the full set of motion vectors. This extraction approach allows the system to focus computational resources on the most relevant motion data for identifying in-vehicle objects, reducing overall processing complexity while maintaining detection comprehensiveness
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 solution enables precise detection of in-vehicle objects by accurately differentiating between motion vectors associated with vehicle acceleration and those outside the vehicle, improving the accuracy of object identification within the vehicle.
Implementation Method 1
an acceleration detection unit configured to detect an acceleration
Data Source
AI summary
A control apparatus includes an acceleration detection unit that detects an acceleration, and a processor and memory storing instructions that when executed by the processor, cause the control apparatus to determine a motion vector from video data within a vehicle obtained by an image capturing unit fixed in the vehicle, determine whether there is a correlation between an amount of change of a determined motion vector in a preset period and the detected acceleration in the preset period for each position in the video data, and determine, based on a result of the determination for each position, as an out-of-vehicle region, a region in which an object outside of the vehicle within the video data appears.