Object Spin Estimation Using Marker Segmentation Maps
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Solution Overview
Problem
Capturing accurate spin-related properties of moving objects, such as spin rate and spin axis, is challenging due to high speeds and the aliasing effects that occur when cameras operate below the necessary framerate to capture these properties.
Innovation Solution
A spin-estimation system that applies predefined marker patterns to the object, captures images from multiple orientations, generates object marker segmentation maps, and uses deep-learning models to estimate spin rate and axis, with post-processing algorithms to refine the estimations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the camera operates at a lower framerate to reduce data processing load, then energy consumption and device complexity are reduced, but measurement precision of spin rate deteriorates due to aliasing effects
Solution Approach 1:
The patent applies preliminary action by pre-processing images to isolate the object and generate segmentation maps before spin estimation. This prepares the data in advance, allowing accurate spin measurement from fewer frames, thereby reducing the required framerate while maintaining precision.
Solution Approach 2:
The patent extracts the essential spin information by isolating the object from the background and focusing analysis only on the object's marker patterns. This extraction allows accurate spin rate measurement without needing to process entire high-resolution frames at high framerates, reducing overall system complexity.
2Measurement precision
If the image capture framerate is increased to capture high spin rates accurately, then measurement precision of spin rate improves, but energy consumption and data processing load increase
Solution Approach 1:
By performing object isolation and segmentation map generation as preliminary steps, the system prepares processed data that contains only essential information. This allows spin rate to be accurately measured from lower framerate captures, significantly reducing energy consumption while maintaining measurement precision.
Solution Approach 2:
The system extracts only the necessary spin-related features from images through object isolation and marker pattern recognition. This selective extraction reduces the amount of data that needs to be processed and stored, lowering energy consumption while preserving accurate spin measurement capability.
3Measurement precision
If multiple images from multiple orientations are captured to improve spin estimation accuracy, then measurement precision of spin axis improves, but loss of time increases due to additional capture and processing steps
Solution Approach 1:
The system performs preliminary object isolation and generates segmentation maps from captured images before spin estimation. This pre-processing organizes the data structure in advance, enabling efficient processing of multiple orientations and reducing the total time required for accurate spin axis estimation.
Solution Approach 2:
The segmentation map serves as an intermediary data structure that consolidates object information from multiple images. This intermediate representation allows the spin estimation algorithm to efficiently process multiple orientations without repeatedly analyzing raw images, reducing computational time while maintaining accuracy.
Data Source
AI summary
A spin-estimation system may include an image-capturing sensor positioned and configured to capture images of an object within a field of view of the image-capturing sensor. The spin-estimation system may be configured to perform one or more operations to analyze spin properties of the object. The operations may include setting an image capture framerate that corresponds to a minimum spin motion of the object, printing an orientation marker on an outer surface of the object, and capturing, by the image-capturing sensor at the set image capture framerate, images of the object after starting motion of the object. The operations may include isolating the object in each image to generate isolated object images. The operations may include generating an object marker segmentation map based on the isolated object images. A spin rate and a spin axis may be estimated based on the object marker segmentation map using deep learning approaches.