Camera Speed Estimation Using Pixel Intensity Minimization
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Solution Overview
Problem
Existing methods for estimating the speed of a video camera while capturing a three-dimensional scene are complex and prone to noise, especially when dealing with rolling shutter distortion and motion blur, and often require feature extraction and matching steps.
Innovation Solution
A method that directly minimizes differences in physical magnitudes across a large number of pixels in both reference and current images, eliminating the need for feature extraction and matching, and accounts for camera movement to accurately estimate speed, even in the presence of rolling shutter and motion blur distortions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If feature-based methods are used to estimate camera speed, then the estimation can be performed, but the method becomes complex and noisy due to feature extraction and matching steps
Solution Approach 1:
The patent extracts only the essential information needed for speed estimation by directly using pixel intensity values from the image, eliminating the complex feature extraction and matching steps. This removes the noisy intermediate processing while retaining the core measurement capability, thereby reducing method complexity without sacrificing estimation accuracy.
Solution Approach 2:
The patent replaces the mechanical feature-based processing system with a direct pixel intensity comparison approach. Instead of extracting features, matching them across frames, and deriving speed, the method directly minimizes differences in physical magnitudes (pixel intensities) between reference and current images, substituting a simpler computational mechanism that achieves the same goal with less complexity.
2Reliability
If feature extraction and matching steps are used, then camera speed can be estimated, but noise and complexity increase
Solution Approach 1:
The patent removes the noisy feature extraction and matching steps entirely, keeping only the essential direct comparison of pixel intensities. This extraction of the core measurement principle eliminates the intermediate processing stages that introduce noise, thereby improving reliability by reducing the number of operations where errors can be introduced.
Solution Approach 2:
The patent uses a reference image that is a direct copy or representation of the scene at a previous time point, comparing it directly with the current image. This approach avoids the need to extract and match features between frames, using instead a straightforward intensity comparison that is less susceptible to noise and more reliable.
3Productivity
If rolling shutter distortion is present, then image capture is faster, but distortion increases requiring complex correction
Solution Approach 1:
The patent converts the rolling shutter distortion, which is typically a harmful effect, into useful information for speed estimation. By directly comparing pixel intensities between reference and current images and minimizing the differences, the method leverages the temporal offset inherent in rolling shutter capture to infer camera motion, thereby transforming the distortion from a problem to be corrected into a signal that provides speed information.
4Duration of action of moving object
If motion blur is present, then exposure time can be longer, but image quality deteriorates
Solution Approach 1:
The patent converts motion blur, which normally degrades image quality, into a useful signal for speed estimation. By directly comparing pixel intensities between reference and current images and minimizing the differences, the method extracts speed information from the motion blur pattern itself, thereby transforming the quality degradation into a measurement opportunity that provides accurate speed data.
Data Source
AI summary
A method for estimating the speed a first video camera when it captures a current image of a three-dimensional scene, the current image including pixels. The method includes storing a reference image corresponding to an image of the same scene captured by a second video camera in a different pose, the reference image including pixels. The method also includes storing the current image, containing for each pixel of the current image the measurement of a physical magnitude measured by that pixel, which is the same as the physical magnitude measured by the pixels of the reference image. The method further includes storing for each pixel of the reference image or of the current image the measurement of a depth that separates that pixel from the point of the scene photographed by that pixel, estimating the pose and speed of the first video camera.