Interactive Projector Pointing Detection via Segmented Image Analysis
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Solution Overview
Problem
Existing interactive projectors face challenges in accurately detecting pointing elements due to image distortion and varying sizes of pointing elements across the projected screen, leading to suboptimal detection results when using a single parameter for image processing.
Innovation Solution
The interactive projector segments the image into small areas and applies different detection parameters, including deformation ratios, template images of varying sizes, and resolution conversion, to improve detection accuracy by matching suitable parameters to each area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single parameter is used for detection process, then device complexity is reduced, but measurement precision of pointing element detection deteriorates
Solution Approach 1:
The patent divides the taken image into multiple small areas (e.g., left, center, right regions) and applies different detection parameters to each area. This segmentation allows the system to handle local variations in image distortion and pointing element size without requiring a completely complex detection system, thus improving detection accuracy while keeping the overall process manageable.
Solution Approach 2:
Different detection parameters are assigned to different regions of the image based on their specific characteristics. For example, areas with higher distortion or different magnification ratios use specialized parameters optimized for those conditions. This local quality approach enables precise detection in each region while maintaining system simplicity through targeted parameter application rather than universal complexity.
2Measurement precision
If template matching is performed without considering local distortion, then processing time is reduced, but measurement precision of pointing element position deteriorates
Solution Approach 1:
The image is segmented into multiple small areas, and template matching is performed independently in each area using parameters optimized for that specific region. This allows the system to maintain high detection precision by accounting for local distortion characteristics while limiting the processing time impact to only the relevant regions rather than the entire image.
Solution Approach 2:
The patent changes detection parameters (such as template size, matching threshold, or correlation coefficients) based on the local characteristics of each image region. By adapting parameters to match the distortion and magnification ratios of specific areas, the system achieves accurate position detection without requiring excessive processing time across the entire image.
3Measurement precision
If uniform detection parameters are applied across the entire image, then ease of operation is improved, but measurement precision deteriorates due to varying distortion and size
Solution Approach 1:
The detection process is segmented into region-specific operations where each area receives tailored parameters. This segmentation maintains ease of operation by following a systematic regional approach rather than requiring complex global adjustments, while simultaneously improving precision through localized optimization for distortion and size variations.
Solution Approach 2:
The system implements local quality by applying different detection parameters to different regions based on their specific distortion and magnification characteristics. This approach preserves operational simplicity through a structured regional framework while achieving high measurement precision through customized parameter application in each area.
Data Source
AI summary
An interactive projector includes a projection section adapted to project a projected screen on a screen surface, an imaging section adapted to take an image of an area of the projected screen, and a pointing element detection section adapted to perform a detection process for detecting the pointing element based on the taken image, which is taken by the imaging section, and includes the pointing element, and the pointing element detection section sections the taken image into a plurality of small areas, and performs the detection process in at least one of the small areas using a parameter different from parameters in the rest of the small areas.