Video Analytics Engine for Retail Activity Inference
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Solution Overview
Problem
Conventional methods for monitoring retail business processes are inefficient and costly, requiring substantial human resources to analyze video data from CCTV cameras across multiple locations, making it impractical to monitor all desirable areas simultaneously.
Innovation Solution
An automated video surveillance system employing a video analytics engine to process video data, generate video primitives, and an activity inference engine to determine predefined activities of interest, reducing the need for manual observation and enabling real-time or offline analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual observation and analysis of video data from CCTV cameras is used, then business intelligence data can be extracted, but substantial human resources and expenses are required
Solution Approach 1:
The patent replaces the mechanical system of manual human observation and analysis with an automated video analytics system comprising video processing modules, pattern recognition algorithms, and data analysis software. This substitution eliminates the need for substantial human resources while maintaining the ability to extract business intelligence data from video feeds.
Solution Approach 2:
The video analytics system performs self-service by automatically processing video data, detecting patterns, generating insights, and producing reports without requiring human intervention. The system autonomously executes the complete workflow from video acquisition to intelligence extraction, reducing operational complexity and costs.
2Area of stationary object
If CCTV cameras are placed in all desirable locations, then comprehensive monitoring coverage is achieved, but monitoring all video requires substantial human resources
Solution Approach 1:
The patent replaces manual monitoring with automated video analytics technology that can simultaneously process multiple video streams from numerous cameras across all desirable locations. This enables comprehensive coverage without proportionally increasing human resources, as the automated system handles multiple feeds concurrently.
Solution Approach 2:
The video analytics system provides multi-functional capabilities by simultaneously performing multiple tasks across all camera locations including motion detection, pattern recognition, event classification, and data extraction. This universal system handles diverse monitoring requirements across the entire facility through a single integrated platform.
3Loss of information
If remote human observers monitor video from multiple locations, then business process monitoring is performed, but costs and time consumption increase substantially
Solution Approach 1:
The patent replaces remote human observers with automated video analytics processing that continuously analyzes video streams in real-time or near real-time. This substitution dramatically reduces analysis time while maintaining comprehensive business process monitoring capability across multiple locations simultaneously.
Solution Approach 2:
The video analytics system operates continuously without interruption, processing video data from all locations constantly. This continuous automated operation eliminates the time consumption associated with manual monitoring schedules, breaks, and human fatigue, providing uninterrupted business process monitoring.
Data Source
AI summary
A system for video monitoring a retail business process includes a video analytics engine to process video obtained by a video camera and generate video primitives regarding the video, A user interface is used to define at least one activity of interest regarding an area being viewed, each activity of interest identifying at least one of a rule or a query regarding the area being viewed. An activity inference engine processes the generated video primitives based on each defined activity of interest to determine if an activity of interest occurred in the video.


