Real-time Object Relevance Detection via Shape Analysis
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Solution Overview
Problem
Existing real-time computer vision systems struggle to accurately determine the relevance of objects in a surrounding environment, particularly in dynamic scenarios like autonomous vehicles, where the position and orientation of objects change.
Innovation Solution
A computer-implemented method that captures images of a surrounding environment, identifies objects using computer vision algorithms, determines the relevance of objects based on their shape and aspect ratio, and performs operational actions accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If computer vision algorithms are used to recognize objects in real-time, then object recognition accuracy and speed are improved, but the ability to determine object relevance to the capturing entity deteriorates
Solution Approach 1:
The patent transitions from two-dimensional image recognition to three-dimensional spatial reasoning by analyzing the shape and position of objects relative to the capturing entity. This dimensional addition enables the system to determine relevance by assessing whether an object's geometric properties and spatial relationship indicate interaction or importance to the entity, thereby resolving the contradiction between recognition accuracy and relevance determination capability.
2Productivity
If real-time image processing is performed to identify objects, then processing speed is improved, but the complexity of analyzing object shape and relevance increases
Solution Approach 1:
The patent extracts and focuses analysis only on the shape and position attributes of objects that are most indicative of relevance to the capturing entity. By selectively extracting these specific geometric properties rather than analyzing all possible object characteristics, the system maintains high processing speed while achieving effective relevance determination, thus resolving the contradiction between productivity and complexity.
3Reliability
If detailed object analysis including shape and position is performed, then object relevance is improved, but computational resources and processing time are worsened
Solution Approach 1:
The patent applies local quality analysis by focusing computational resources only on the specific local attributes of objects that matter for relevance determination - namely shape and position relative to the capturing entity. This localized analysis approach avoids exhaustive processing of all object properties, thereby maintaining high reliability in relevance determination while reducing overall computational energy consumption.
Data Source
AI summary
A computer-implemented method, a computer system and a computer program product recognize relevant objects in images in real time. The method includes capturing an image of a surrounding environment using a device. The method also includes identifying an object and a shape of the object in the image of the surrounding environment using a computer vision algorithm. The method further includes determining that the object is a relevant object based on the shape of the object. Lastly, the method includes performing an operational action based on the relevant object.