Object Recognition System Using Dynamic Detection Strategy Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional object recognition schemes are inefficient and computationally expensive, failing to effectively identify objects in images due to their inability to utilize composite attributes effectively.
Innovation Solution
A system and method that employs a combination of independent and joint detection strategies using a processor and memory-based system to identify objects in images by training detectors on both individual and composite attributes, selecting the most effective strategy based on cross-validation and regression analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional object recognition schemes use independent attributes for identification, then the system is simpler to implement, but the object identification efficiency and effectiveness deteriorate
Solution Approach 1:
The system dynamically selects between independent and joint detection strategies based on the specific object and attributes being detected. This dynamic adaptation allows the system to optimize performance for each detection task rather than using a fixed approach, resolving the contradiction between system simplicity and detection efficiency.
Solution Approach 2:
The system changes the detection parameters by switching between independent attribute detection and joint composite attribute detection based on the specific detection scenario. This parameter change enables the system to achieve high efficiency without requiring constant complexity, as it adapts the detection approach to match the detection needs.
2Measurement precision
If conventional schemes use composite attributes for object identification, then the identification effectiveness improves, but the computational cost and time consumption increase
Solution Approach 1:
The system applies joint composite attribute detection selectively only when necessary, rather than always using the most computationally intensive method. By using independent detection for simple cases and reserving joint detection for complex scenarios, the system achieves high identification effectiveness without incurring excessive computational costs for all detections.
Solution Approach 2:
The detection process is segmented into two distinct strategies: independent attribute detection and joint composite attribute detection. The system divides the detection space and applies the appropriate strategy based on the specific object and attribute combination, allowing efficient processing for simple cases while maintaining high effectiveness for complex cases.
3Adaptability or versatility
If the system trains multiple detection strategies, then the adaptability and performance improve, but the training complexity and resource requirements increase
Solution Approach 1:
The system implements a universal selection mechanism that can choose between independent and joint detection strategies based on the specific detection task. This universal selector module allows the system to maintain high adaptability across different detection scenarios without requiring separate specialized systems for each detection type, thus managing training complexity while preserving versatility.
Data Source
AI summary
There is provided a system configured to receive a plurality of images, analyze a set of features of the plurality of images to determine a difference between a first training performance of a plurality of independent detectors based on one or more of individual attributes and a second training performance of a plurality of joint detectors based on one or more of composite attributes, select, based on the analyzing, either one of the plurality of independent detectors or one of the plurality of joint detectors for identifying a plurality of objects in the plurality of images, and identify the plurality of objects in the plurality of images, using the selected one of the plurality of independent detectors utilizing the one or more of the individual attributes or using the selected one of the plurality of joint detectors utilizing the one or more of the composite attributes.