Input Data Management Architecture for Gesture Tracking
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Solution Overview
Problem
Conventional approaches fail to effectively manage and propagate user input data, such as gestures and head movements, to applications and services on portable computing devices, leading to inefficiencies in interaction and control.
Innovation Solution
A system architecture that utilizes cameras and motion sensors to track user inputs, processes the data, and provides it to clients through both push and pull methods, using filters for smoothing and synchronization, enabling improved correlation and management of user gestures, head movements, and device rotations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional approaches are used to manage user input data, then device complexity is reduced, but user interaction reliability and input data propagation effectiveness deteriorate
Solution Approach 1:
The patent introduces an input data management layer that acts as an intermediary between raw input data from sensors/cameras and applications. This layer includes components for data collection, filtering, synchronization, and distribution, thereby improving reliability without requiring applications to directly handle complex sensor data processing.
Solution Approach 2:
The input data management system is segmented into distinct functional modules: data collection from multiple sources, filtering processing, synchronization mechanisms, and distribution to clients. This segmentation allows each module to specialize in specific tasks, improving overall reliability while keeping individual components manageable in complexity.
2Measurement precision
If multiple data sources (cameras, motion sensors) are integrated to track user inputs, then measurement precision of user gestures improves, but device complexity increases
Solution Approach 1:
The patent merges data from multiple sources (cameras, motion sensors, gyroscopes) into a unified input data stream. By combining these diverse data sources through a common management interface and synchronization mechanism, the system achieves higher measurement precision for gesture recognition while abstracting away the complexity of individual sensor integrations.
Solution Approach 2:
The input data management layer provides universal functionality for handling various types of input data from different sources. It implements a standardized interface that can process camera data, motion sensor data, and other input types uniformly, thereby improving measurement precision across multiple sensor types without requiring separate handling logic for each.
3Reliability
If data filtering and synchronization processes are applied to input data, then data propagation reliability improves, but processing time increases
Solution Approach 1:
The system performs preliminary filtering and synchronization of input data as it is collected, before the data needs to be propagated to applications. By preparing the data in advance through these processing steps, the system ensures high data propagation reliability while minimizing the time penalty during actual data delivery to clients.
Solution Approach 2:
The input data management layer operates continuously to filter and synchronize data streams from multiple sources. This continuous processing ensures that data is always ready for propagation without intermittent processing delays, thereby maintaining high reliability while minimizing overall processing time through steady-state operation.
Data Source
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AI summary
A tracking architecture is provided that enables data for gestures and head positions to be provided to both native and non-native clients on a computing device. A pipeline component can obtain the raw image data and sensor data and synchronize that data to be processed to determine, for example, location and/or motion data that may correspond to device input. The data can be processed by separate components, such as an event publisher and an event provider, each capable of filtering the location, motion, and/or raw sensor data to generate a set of event data. The event data then can be published to registered listeners or provided in response to polling requests. Head coordinates, gesture data, and other such information can be passed through one or more interface layers enabling the data to be processed by a non-native client on the device.