Mobile Entity Detection Using Optical Flow Clustering and Vehicle Motion Filtering
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Solution Overview
Problem
Existing mobile entity detection systems falsely detect stationary objects like road markings, parked vehicles, or signboards as moving entities due to their relative movement with the vehicle, leading to inaccurate detection.
Innovation Solution
A mobile entity detection apparatus that calculates unbiased variance of luminance change, extracts feature points using the FAST algorithm, performs optical flow specification and clustering, tracks overlapping clusters, and filters out background clusters based on vehicle direction and speed to accurately distinguish between mobile entities and background objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If optical flow selection based on vanishing point intersection is used to detect mobile entities, then mobile entity detection can be achieved, but false detection of stationary background objects occurs
Solution Approach 1:
The patent segments the detection process into multiple stages: initial mobile entity detection using vanishing point intersection, followed by separation of optical flows into background and foreground components, and final verification by comparing foreground optical flows with vehicle movement. This segmentation allows the system to maintain detection capability while eliminating false positives from stationary objects.
Solution Approach 2:
The patent introduces an intermediary verification mechanism using vehicle movement data as a reference. By comparing the movement characteristics of detected optical flows against known vehicle movement patterns, the system acts as a mediator to distinguish true mobile entities from false detections caused by stationary background objects.
2Productivity
If vanishing point-based optical flow selection is applied, then mobile entities can be detected, but stationary objects like road markings and parked vehicles are falsely detected as mobile
Solution Approach 1:
The patent divides optical flows into separate background and foreground components through a dedicated separation process. Background optical flows (including stationary objects) are isolated and excluded from final detection results, while foreground optical flows representing true mobile entities are retained. This segmentation maintains comprehensive detection coverage while eliminating false detections.
Solution Approach 2:
The patent extracts and removes background optical flows from the detection process by identifying their characteristic patterns (such as movement consistent with vehicle motion only) and separating them from foreground mobile entities. This extraction process eliminates stationary objects like road markings and parked vehicles from false detection while preserving true mobile entity detection.
3Measurement precision
If comprehensive optical flow analysis is performed to improve detection accuracy, then detection precision increases, but system complexity increases
Solution Approach 1:
The patent segments the complex optical flow analysis into distinct, manageable modules: vanishing point calculation, optical flow extraction, background-foreground separation, and verification against vehicle movement. Each module performs a specific function with well-defined inputs and outputs, making the overall complex system more manageable and implementable while maintaining high detection accuracy.
Data Source
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AI summary
A mobile entity detection apparatus 10 includes: a feature point extraction unit 11 configured to extract, from image data output by an imaging device of a vehicle, a feature point moving in an image; an optical flow specification unit 12 configured to compare the latest image data with image data that was output in the past, and specify an optical flow for each feature point; a clustering unit 13 configured to perform clustering on the optical flow based on the optical flow and the position of the optical flow in the image, and separate the optical flow into a cluster; a filtering unit 14 configured to remove a cluster that corresponds to an object forming a background from among the clusters based on the traveling direction and speed of the vehicle; and a mobile entity specification unit 15 configured to specify a mobile entity in the image using a result of clustering after cluster removal.