Motion Data Capture with Context Embedding for Accurate Interpretation
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Solution Overview
Problem
Current motion capture technologies face challenges in accurately interpreting and processing motion information by machines, as the meaning of movements can vary significantly based on context, and existing systems lack effective methods to provide necessary context data for reliable interpretation.
Innovation Solution
The method involves a capturing device converting motion information into a digital signal, which is then embedded in a data sequence transmitted to a receiver, including context data that defines the meaning of the motion within a specific context, such as text strings or keywords, allowing machines to accurately interpret and process the motion information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If motion information is transmitted without context data, then transmission efficiency is improved, but interpretation accuracy deteriorates
Solution Approach 1:
The patent applies preliminary action by embedding context data (such as text strings, keywords, or labels) into the data sequence before transmission. This context data is prepared in advance to define the meaning of motion information within a specific context, enabling the receiver to accurately interpret the motion without requiring complex post-processing or additional communication rounds.
2Measurement precision
If context data is added to the data sequence, then interpretation accuracy is improved, but data transmission complexity increases
Solution Approach 1:
The patent uses context data as an intermediary element that mediates between the motion capture device and the receiver. This context data (text strings, keywords, or labels) serves as a bridge that provides meaning to the motion information, enabling accurate interpretation without requiring the receiver to have complex interpretation algorithms or extensive knowledge bases.
3Loss of information
If motion information is captured in detail, then information completeness is improved, but processing difficulty increases
Solution Approach 1:
The patent applies the extraction principle by separating motion information from its contextual meaning. The context data is extracted and embedded alongside the motion data in the data sequence. This separation allows the receiver to process motion information and context data independently, then combine them for accurate interpretation, reducing overall processing difficulty while maintaining information completeness.
Data Source
AI summary
In a method for capturing and transmitting motion data (s1) from a transmitter (103, 203) to a receiver (104, 204), motion data is captured by a capturing device (102, 202) at the transmitter end, said capturing device (102, 202) registering the motion of an object (106, 206) by means of at least one sensor (101, 201) and converting the registered motion into a digital signal (i2). Said digital signal is fed to the receiver, which embeds the data of the digital signal (i2) in a series (i3) of data and transmits said series of data to a receiver. In addition to or instead of the data of the digital signal, the series of data transmitted by the transmitter contains context data which the receiver uses to interpret and process the originally captured motion data within a defined context.