Motion Determination Apparatus Using Scalar Representations
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Solution Overview
Problem
Current technologies face challenges in accurately determining and interpreting motion from video data, particularly in identifying specific motions and postures, which limits their efficiency and versatility in applications such as user interaction and environmental analysis.
Innovation Solution
An apparatus comprising a processor and memory that receives video data, generates scalar and vector representations of movement, and identifies predetermined motions by correlating these representations with reference data, allowing for efficient determination of motion and posture without requiring tracking or segmentation calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional motion determination methods are used, then motion can be detected, but accuracy in identifying specific motions and postures deteriorates
Solution Approach 1:
The patent extracts and removes the complex tracking and segmentation calculation components from the motion determination system. Instead of using traditional methods that require tracking object boundaries and segmenting video frames, the invention directly compares video data against reference motion patterns, eliminating the need for complex intermediate processing steps while maintaining or improving motion identification accuracy.
Solution Approach 2:
The patent replaces the mechanical/computational system of tracking and segmentation with a pattern recognition approach. Rather than mechanically tracking object boundaries through multiple calculation steps, the system substitutes this with a direct comparison mechanism that matches video input against predetermined motion patterns, significantly reducing computational complexity while improving precision.
2Measurement precision
If complex tracking and segmentation calculations are performed, then detailed motion analysis is achieved, but processing efficiency deteriorates
Solution Approach 1:
The patent extracts and eliminates the time-consuming tracking and segmentation calculation steps from the processing pipeline. By directly comparing video input against reference motion patterns, the system achieves detailed motion analysis without the computational overhead of traditional methods, thereby significantly improving processing efficiency while maintaining analytical detail.
Solution Approach 2:
The patent performs preliminary action by pre-establishing reference motion patterns and postures before actual motion determination. These reference patterns are created in advance and stored for quick comparison, eliminating the need to perform complex analysis during real-time processing. This preliminary preparation enables fast, efficient motion recognition while maintaining detailed analysis capabilities.
3Adaptability or versatility
If traditional motion determination methods are used, then basic motion detection is possible, but versatility in gesture interaction deteriorates
Solution Approach 1:
The patent implements universality by creating a motion determination system that can handle multiple types of motions and gestures through a single unified approach. The reference pattern library encompasses diverse motion types, allowing the system to accurately identify various gestures, postures, and movements without requiring separate specialized algorithms for each type, thereby enhancing versatility while keeping system complexity manageable.
Data Source
AI summary
An apparatus comprising a processor and a memory that cause the apparatus to perform receiving a video indicating a motion, generating a set of scalar representations of movement based, at least in part, on at least part of the video, and identifying at least one predetermined motion that correlates to the set of scalar representations of movement is disclosed.