Video Waveform Reconstruction for Motion Clarity
Solution Overview
Problem
Conventional video recording techniques suffer from sampling rate limitations and data storage constraints, leading to distorted visual representations of motion due to insufficient samples per cycle, especially when analyzing higher frequencies, and traditional filtering methods introduce noise and computational inefficiencies.
Innovation Solution
The implementation of improved time domain reconstruction methods that allow for the reconstruction of video waveforms with a higher number of samples per cycle, reducing noise and enhancing visual quality by isolating specific frequencies of interest, thereby overcoming the limitations of frequency domain filtering techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional frequency domain filtering techniques are used to isolate frequencies of interest, then the visual representation of motion can be enhanced, but distortion effects appear at the beginning and end of the data set and enveloping occurs throughout the data
Solution Approach 1:
The patent extracts only the specific frequency components of interest from the video data using Fourier transform analysis, separating them from the rest of the spectrum. This allows precise frequency isolation while avoiding the distortion effects that occur with traditional filtering methods that modify the entire data set.
Solution Approach 2:
The patent creates a synthetic copy of the waveform at the selected frequency using the amplitude and phase information obtained from the Fourier transform. This copied waveform is then overlaid on the original video, providing a clean visual representation without the distortion artifacts that would result from directly filtering the original data.
2Measurement precision
If data is captured at extremely high sampling rates for long durations to improve visual quality, then more samples per cycle are available for higher frequencies, but data storage requirements and computation times increase dramatically
Solution Approach 1:
The patent replaces the mechanical approach of capturing high-rate video data with a mathematical approach using Fourier transform analysis. Instead of increasing the sampling rate of the camera, the system processes the existing video frames to extract frequency information, dramatically reducing storage requirements while maintaining the ability to analyze high frequencies.
Solution Approach 2:
The patent changes the parameter of interest from temporal resolution (sampling rate) to frequency domain representation. By transforming the data into the frequency domain using Fourier analysis, the system can identify and visualize specific frequency components without requiring high sampling rates, thus reducing data storage needs while improving frequency analysis capability.
3Adaptability or versatility
If traditional filtering methods are applied to finite video data sets, then frequencies of interest can be isolated, but distortions occur at the beginning and end of the data set
Solution Approach 1:
The patent performs preliminary Fourier transform analysis on the entire video data set before reconstructing the waveform. This allows the system to identify the exact frequency components and their characteristics (amplitude, phase) in advance, enabling accurate waveform synthesis without the edge distortions that occur when filtering is applied directly to the video frames.
Solution Approach 2:
The patent creates a synthetic copy of the desired frequency waveform using the spectral information obtained from the Fourier transform. This copied waveform is constructed mathematically with the correct amplitude and phase, ensuring accurate representation without the distortion artifacts that would result from traditional filtering methods applied to the original video data.
Data Source
AI summary
A source video of a scene showing moving objects, undergoing periodic motion in a field of view which may be located in a region of interest, is filtered and processed by constructing a representation such as a frequency spectrum plot of some of the frequencies of motion in the scene or region of interest and enabling a selection of frequency peaks representing one or more pixels in the field of view from which to generate reconstructed waveforms, then applying the reconstructed waveform at each pixel to a reference frame to produce a modified video recording.