Risky Behavior Detection via Silhouette Distance Analysis
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Solution Overview
Problem
Conventional surveillance systems for detecting risky behavior require operator analysis and often infringe on individuals' privacy by capturing video images, leading to unsatisfactory surveillance quality and comfort issues.
Innovation Solution
A detection network utilizing an artificial neural network to analyze temporal sequences of silhouette distances from topographic views, eliminating the need for video image capture and enabling autonomous detection of risky behavior without operator intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video images are captured to detect risky behavior, then detection accuracy is improved, but privacy protection deteriorates
Solution Approach 1:
The patent extracts only the essential information needed for detection (silhouette and distance data) from the complete video image, discarding all non-essential visual information that would compromise privacy. This allows detection to proceed with minimal data collection, resolving the contradiction between accuracy and privacy.
Solution Approach 2:
Instead of using actual video images, the system creates simplified representations (silhouettes) that capture only the necessary spatial and temporal information for behavior analysis. This copy contains sufficient detection data while eliminating privacy-sensitive details.
2Adaptability or versatility
If operator analysis is used to detect risky behavior, then detection flexibility is improved, but productivity deteriorates
Solution Approach 1:
The system enables automatic detection through algorithmic analysis of silhouette sequences, allowing the surveillance system to serve itself without human intervention. The artificial intelligence processes the data autonomously, maintaining flexibility while dramatically improving productivity and efficiency.
3Area of stationary object
If video cameras are deployed to monitor living areas, then surveillance coverage is improved, but ease of operation deteriorates
Solution Approach 1:
The system extracts only silhouette and distance information from the monitored space, removing the need for comprehensive video imaging. This minimal data collection approach maintains surveillance coverage while significantly improving user comfort and acceptance by eliminating intrusive visual monitoring.
Data Source
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AI summary
The invention relates to a detection device comprising: - a depth sensor (28) configured to generate a plurality of topographic views of the detection field (24), each topographic view comprising topographic distances between the depth sensor (28) and points within the detection field (24), - a determination module (30) configured to determine a silhouette of the person (22) from at least one topographic view, the silhouette being defined by a subset of the topographic distances, referred to as silhouette distances, - a processing module (32) configured to determine the risky behavior of the person (22) by propagating at least one temporal sequence of silhouette distances via an artificial neural network. The artificial neural network is trained on a temporal sequence of silhouette distances corresponding to reference behaviors of the person (22).