Image Summarization System for CCTV Event Analysis
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Solution Overview
Problem
Current image summarization methods for CCTV systems are inefficient as they require users to repeatedly review extensive video recordings, lack consideration for user-defined parameters like image speed and object display, and necessitate storing large original images for event analysis, leading to storage and time management issues.
Innovation Solution
An image summarization system and method that extracts background frames and object information, selects relevant objects as a queue, and generates summarized videos based on user-defined regions of interest, reducing the need for extensive storage and review time by presenting only critical information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If simple summarization methods (skipping frames or extracting events/objects) are used, then the summarization process is fast and simple, but the user cannot efficiently examine the summarized content and must repeatedly review the image
Solution Approach 1:
The patent segments the video content by extracting and displaying multiple objects simultaneously in a single frame, rather than showing sequential frames. Each object is identified, tracked, and presented with its key information (type, location, time) in a structured layout, allowing users to examine multiple events at once without repeated reviewing
Solution Approach 2:
The patent transforms the temporal dimension of video playback into a spatial arrangement by displaying multiple objects from different time points within a single summarized frame. Objects are positioned according to their spatial coordinates in the original video, creating a multi-dimensional view that preserves both temporal and spatial information simultaneously
2Measurement precision
If original images are stored to obtain event and object information, then accurate analysis is possible, but large storage capacity is required
Solution Approach 1:
The patent extracts only the essential information needed for event analysis (object type, location, time, and key attributes) from the original video frames and stores this structured data separately. This extraction approach maintains measurement precision for event analysis while dramatically reducing the storage requirement from full-resolution video frames to compact information records
Solution Approach 2:
The patent creates simplified copies of the original video content in the form of structured object information and metadata. These copies contain all necessary analytical data (object characteristics, temporal-spatial information, event types) without requiring storage of the original large-capacity video files, enabling accurate event analysis from the compact copies
3Reliability
If all objects in CCTV images are monitored, then comprehensive security coverage is achieved, but the number of objects to track becomes overwhelming and reduces operational efficiency
Solution Approach 1:
The patent applies local quality by allowing users to define regions of interest (ROI) within the surveillance area. Objects within these designated regions receive enhanced monitoring and detailed tracking, while objects outside these regions are monitored at a lower level or aggregated statistically. This differential monitoring approach maintains comprehensive security coverage while focusing operational attention on critical areas
Solution Approach 2:
The patent changes the monitoring parameters dynamically based on object characteristics, location, and user-defined priorities. Objects in regions of interest are tracked with higher detail and lower thresholds for alert generation, while other objects use aggregated or reduced monitoring parameters. This parameter adjustment maintains reliability for critical areas while improving overall operational efficiency
Data Source
AI summary
To summarize an input image, an image summarization system extracts a background frame and object information of each of objects from an image stream, and receives a region of interest set in a predetermined region of the background frame. The image summarization system selects the extracted objects as queue objects, and generates a summarized video based on the queue object, the background frame, and the region of interest.