Enclosed Space Object Tracking via Frame Linking
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Solution Overview
Problem
Existing object tracking algorithms are inadequate for accurately tracking objects in enclosed spaces with greater formal changes, as they are primarily designed for open spaces and lack specificity in monitoring environments with varying object properties and movements.
Innovation Solution
An image-based object tracking method and system that analyzes a video stream from an enclosed space, using an image capturing device, storage device, and processor to detect moving objects, generate frames, and establish a linking relationship between current and previous frames to track objects accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing object tracking algorithms designed for open spaces are used, then the system can handle objects entering and exiting the monitored space, but the tracking accuracy deteriorates for objects in enclosed spaces with greater formal changes
Solution Approach 1:
The patent applies local quality by designing different tracking strategies for different space types. The system identifies whether the monitored space is enclosed or open and applies the appropriate algorithm: enclosed space algorithms for fixed-range tracking in enclosed environments, and open space algorithms for monitoring objects entering/exiting. This localized adaptation resolves the contradiction by optimizing tracking accuracy for each specific space type rather than using a single general-purpose algorithm.
Solution Approach 2:
The patent implements dynamics by making the tracking system adaptive and configurable based on the monitored environment. The system can dynamically switch between different tracking algorithms and parameters depending on whether the space is enclosed or open, allowing it to maintain high tracking accuracy across different scenarios while preserving the ability to handle objects entering and exiting in open spaces.
2Adaptability or versatility
If tracking algorithms focus on monitoring moving trends in open spaces, then the system can handle variable numbers of objects, but the tracking accuracy deteriorates for objects with greater formal changes in enclosed spaces
Solution Approach 1:
The patent applies local quality by implementing space-type-specific tracking algorithms. For enclosed spaces, the system uses algorithms optimized for tracking objects with greater formal changes, while for open spaces, it uses algorithms designed for handling variable object numbers. This localized approach resolves the contradiction by providing high tracking accuracy for each specific scenario.
Solution Approach 2:
The patent implements universality by creating a multi-functional tracking system that can handle both enclosed and open space scenarios. The system incorporates multiple tracking algorithms and can switch between them based on the monitored environment, allowing it to simultaneously maintain high tracking accuracy for objects with formal changes in enclosed spaces and the ability to handle variable object numbers in open spaces.
3Adaptability or versatility
If a general-purpose tracking algorithm is used, then the system can be applied to various scenarios, but the tracking accuracy deteriorates for specific enclosed space monitoring
Solution Approach 1:
The patent applies segmentation by dividing the tracking system into specialized modules for different space types. The system segments the tracking functionality into enclosed space tracking algorithms and open space tracking algorithms, each optimized for its specific scenario. This segmentation resolves the contradiction by providing high tracking accuracy for enclosed spaces while maintaining overall versatility through the modular architecture.
Solution Approach 2:
The patent implements universality by creating a multi-functional tracking system that incorporates both enclosed space and open space algorithms. The system can adapt to various scenarios by selecting the appropriate algorithm based on the monitored environment, thereby maintaining high tracking accuracy in enclosed spaces while preserving broad applicability across different scenarios.
Data Source
AI summary
A method, a system, and a computer-readable recording medium for image-based object tracking are provided. The method includes following steps. A video stream including a plurality of images is received. The video stream is generated through photographing an enclosed space by an image capturing device, and a moving range of a plurality of observed objects is limited to the enclosed space. A plurality of moving objects are detected from the video stream, and frames associated with each of the moving objects are generated for the images. The images include a current image and a previous image. By analyzing position projecting relationship between current frames in the current image and previous frames in the previous image, linking relationship between the current frames in the current image and the observed objects is established. The observed objects in the enclosed space are tracked according to the established linking relationship.