Motion-Vector Monitoring Control for Crowded Entrance-Exit Detection

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Solution Overview

Problem

Existing technologies struggle to accurately detect human behavior in crowded or low-light environments, leading to potential inaccuracies in monitoring passenger alighting and boarding actions.

Innovation Solution

A monitoring control device that divides captured images into blocks, detects motion vectors, and determines object movement based on vector direction and size, without directly identifying the object, to infer behavior and notify appropriate actions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If human detection is performed based on video data, then passenger alighting act can be determined, but detection accuracy deteriorates when multiple passengers overlap or in low illumination conditions

Engineering Contradiction:

Improvedetection accuracyVSAvoidenvironmental influence

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent divides the captured image into multiple blocks (e.g., 4 blocks: upper left, upper right, lower left, lower right) to segment the monitoring area. By analyzing motion vectors in each block separately, the system can detect passenger movements without being affected by overlapping passengers or low illumination conditions that plague whole-image detection methods.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces motion vectors as an intermediary parameter to infer object behavior. Instead of directly detecting passengers (which fails in crowded/dark conditions), the system detects motion vectors in image blocks and uses these vectors to determine passenger movement toward entrance-exit, thereby avoiding direct detection failures while maintaining monitoring accuracy.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If direct object detection is used, then simple implementation is achieved, but reliability deteriorates in crowded and low-light environments

Engineering Contradiction:

Improvemonitoring reliabilityVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the image into multiple blocks and analyzes motion vectors in each block. This segmentation approach improves reliability by detecting local movements even when passengers are crowded or poorly illuminated, while maintaining relatively simple implementation through standard image processing techniques.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent replaces direct visual detection (which fails in crowded/dark conditions) with motion vector analysis. By substituting the detection mechanism from direct object recognition to motion pattern analysis, the system achieves higher reliability without requiring complex additional hardware or algorithms.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20260004433A1Monitoring control device, monitoring method, and non-transitory storage medium

Publication Date: 2026.01.01 TOYOTA JIDOSHA KK

AI summary

A monitoring control device includes a processor. The processor is configured to monitor the behavior of an object in a predetermined area, based on a captured image in which the area appears. The processor is configured to divide a predetermined range in the captured image into a plurality of blocks, and is configured to detect a motion vector of each of the blocks. The processor is configured to determine, based on a direction and a size of the motion vector of each of the blocks, whether the object moving toward an entrance-exit of the area is present in the captured image, without detecting the object appearing in the captured image.