Video Event Detection for Automatic Object Search Queries
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Solution Overview
Problem
Existing object search techniques in video rely heavily on human intervention, leading to variable search speed and accuracy based on the guard's ability and judgment, which can result in suboptimal performance.
Innovation Solution
An information processing apparatus that automatically analyzes video for event occurrence, determines the type of object to be searched for based on the event, and generates query information to efficiently detect the object at a time other than the event occurrence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual designation by guard is used to initiate person search, then the system can operate with simple architecture, but search speed and accuracy vary depending on guard's ability and judgment
Solution Approach 1:
The system performs self-service by automatically analyzing video data to detect events and generate search queries without requiring manual designation by a guard. The event detection unit autonomously identifies events of interest, and the search query generation unit automatically creates search parameters based on the detected event type, eliminating dependency on human judgment while maintaining system simplicity
Solution Approach 2:
The system performs preliminary action by pre-defining multiple event types and their corresponding search query templates in advance. When an event is detected, the system quickly retrieves and applies the pre-prepared search parameters, enabling rapid response without requiring complex real-time analysis or manual intervention
2Speed
If manual designation by guard is used to initiate search, then the system architecture remains simple, but search speed varies based on guard's response time and judgment
Solution Approach 1:
The system autonomously detects events and generates search queries without waiting for manual input, significantly improving search speed. The event detection unit continuously monitors video data and automatically triggers searches when events are detected, eliminating the bottleneck of manual designation while keeping the system architecture relatively simple
Solution Approach 2:
The system maintains continuous useful action by continuously analyzing video data for event detection rather than waiting for intermittent manual triggers. This continuous monitoring ensures that events are detected and searched for immediately upon occurrence, maximizing search speed and responsiveness
3Measurement precision
If guard manually designates images for search, then the system can use basic processing, but search accuracy lowers when guard does not take optimum action
Solution Approach 1:
The system performs self-service by automatically determining optimal search parameters based on detected event types, eliminating the need for guard judgment. The search query generation unit autonomously selects the most appropriate search criteria depending on the event, ensuring consistently high search accuracy while maintaining ease of operation through automated decision-making
Solution Approach 2:
The system applies dynamics by adapting search parameters dynamically based on the type of event detected. Different event types (e.g., person of interest, abandoned object, suspicious behavior) trigger different search query configurations, allowing the system to optimize search accuracy for each specific situation automatically without requiring manual adjustment
Data Source
AI summary
To efficiency search for an object associated with a sensed event, an information processing apparatus includes a sensor that analyzes a captured video and senses whether a predetermined event has occurred, a determining unit that determines a type of an object to be used as query information based on a type of the event in response to sensing of the event occurrence, and a generator that detects the object of the determined type from the video and generates the query information based on the detected object.