Real-time Video Scale Determination via Aspect Ratio Analysis
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Solution Overview
Problem
Users face difficulties in determining the scale of a viewed scene in photos or videos during capture, as they lack knowledge of image dimensions and object sizes, making it challenging to tune computer vision algorithms accurately.
Innovation Solution
A method is provided where a user adjusts an interactive geometric shape, such as a rectangle, to match objects in the scene, allowing the system to determine the aspect ratio, identify corresponding objects, and set image processing parameters based on the determined resolution, enabling real-time scale estimation without requiring understanding of scale or resolution concepts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually adjust configuration parameters to tune computer vision algorithms, then algorithm accuracy can be improved, but the complexity and difficulty of operation increases significantly
Solution Approach 1:
The system automatically determines image scale and resolution by analyzing the aspect ratio of selected objects, eliminating the need for manual parameter adjustment. The computer vision system performs self-tuning by extracting scale information from the image content itself, thereby maintaining high algorithm accuracy while dramatically reducing operational complexity.
Solution Approach 2:
The patent replaces manual mechanical adjustment of configuration parameters with an automated computational process. Instead of requiring users to manually edit configuration files or adjust sliders, the system uses computer vision algorithms to automatically calculate and set the appropriate scale parameters based on object detection and aspect ratio analysis.
2Measurement precision
If users manually determine image scale and resolution, then accurate parameter setting is achieved, but the time required for setup increases
Solution Approach 1:
The system performs scale determination automatically during the image processing pipeline, eliminating the need for separate manual setup steps. By integrating scale analysis into the object detection and recognition process, the system achieves accurate parameter setting without requiring additional time for user intervention or manual configuration.
Solution Approach 2:
The patent replaces time-consuming manual measurement and calculation of image scale with automated computational algorithms. The system uses computer vision techniques to quickly determine object dimensions, aspect ratios, and resolution parameters, achieving both high accuracy and rapid setup time.
3Reliability
If the system provides detailed scale and resolution information, then accurate object recognition is enabled, but the complexity of the interface and user requirements increase
Solution Approach 1:
The system extracts only the essential scale information needed for object recognition, eliminating unnecessary detailed metadata and complex interface elements. By focusing on key parameters such as aspect ratio and relative object size, the system maintains high recognition accuracy while presenting a simplified interface that requires minimal user input or understanding.
Solution Approach 2:
The patent transforms complex scale and resolution parameters into simplified, intuitive representations. Instead of presenting raw pixel dimensions and resolution values, the system uses normalized aspect ratios and relative size comparisons that are easier to understand and work with, thereby reducing interface complexity while maintaining the precision needed for accurate object recognition.
Data Source
AI summary
Embodiments of the present invention may provide the capability to identify a specific object being interacted with that may be cheaply and easily included in mass-produced objects. In an embodiment, a computer-implemented method for object identification may comprise receiving a signal produced by a physical interaction with an object to be identified, the signal produced by an identification structure coupled to the object during physical interaction with the object, processing the signal to form digital data representing the signal, and accessing a database using the digital data to retrieve information identifying the object.