Orientation-Assisted Image Recognition Search Space Reduction
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Solution Overview
Problem
Conventional image matching algorithms face inefficiencies when dealing with objects captured from varying orientations, leading to increased latency, resource consumption, and false positives, as they often require multiple views of objects to be searched, which expands the search space and complicates the matching process.
Innovation Solution
The system determines the orientation of the camera or computing device used to capture the image, allowing it to limit the search space by matching against images that correspond to the likely view of the object based on the device's orientation, thereby reducing the number of images to be searched and improving processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple views of objects are searched to improve matching accuracy, then the reliability of object recognition is improved, but the productivity decreases due to expanded search space and increased processing time
Solution Approach 1:
The system performs preliminary action by determining the camera orientation before conducting the image matching search. This allows the search space to be pre-filtered to only include images from compatible orientations, avoiding the need to search through all possible views. The orientation determination step is executed in advance, enabling the subsequent matching process to focus only on relevant images, thus maintaining high accuracy while improving processing speed.
2Reliability
If multiple views of objects are searched to reduce false positives, then the reliability of object recognition is improved, but the loss of time increases due to expanded search space
Solution Approach 1:
The system performs preliminary action by determining the camera orientation before conducting the image matching search. This allows the search space to be pre-filtered to only include images from compatible orientations, avoiding the need to search through all possible views. The orientation determination step is executed in advance, enabling the subsequent matching process to focus only on relevant images, thus maintaining high accuracy while improving processing speed.
3Adaptability or versatility
If multiple views of objects are stored to assist matching, then the adaptability of the matching system is improved, but the device complexity increases due to expanded storage and processing requirements
Solution Approach 1:
The system performs preliminary action by determining the camera orientation before conducting the image matching search. This allows the search space to be pre-filtered to only include images from compatible orientations, avoiding the need to search through all possible views. The orientation determination step is executed in advance, enabling the subsequent matching process to focus only on relevant images, thus maintaining high accuracy while improving processing speed.
Solution Approach 2:
The system extracts and utilizes orientation information from the captured image as a filtering criterion. By extracting the orientation parameter and using it to filter the image database, the system reduces the effective search space without requiring storage of multiple views for every object. This extraction approach maintains adaptability while reducing device complexity.
Data Source
AI summary
A user attempting to obtain information about an object can capture image information including a view of that object, and the image information can be used with a matching or identification process to provide information about that type of object to the user. Information about the orientation of the camera and/or device used to capture the image can be provided in order to limit an initial search space for the matching or identification process. In some embodiments, images can be selected for matching based at least in part upon having a view matching the orientation of the camera or device. In other embodiments, images of objects corresponding to the orientation can be selected. Such a process can increase the average speed and efficiency in locating matching images. If a match cannot be found in the initial space, images of other views and categories can be analyzed as well.