Head-Mounted Display Optical Occlusion Target Identification
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Solution Overview
Problem
Wearable computing devices, such as head-mounted displays (HMDs), face challenges in determining which objects among multiple proximate objects the user desires to interact with, as they are typically designed to interact with a predetermined set of objects like the user's body parts, limiting flexibility in interacting with other objects.
Innovation Solution
The HMD employs optical occlusion detection by perceiving a characteristic of a reference object and determining changes caused by a detected object, allowing it to identify the target object for interaction, such as performing optical character recognition on business cards held in the user's hand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the HMD is designed to interact with a predetermined set of objects (e.g., body parts), then the system complexity is reduced and operation is simplified, but the adaptability to interact with other objects is limited
Solution Approach 1:
The HMD automatically identifies target objects by detecting optical occlusion changes in the user's field of view, eliminating the need for manual object selection or predetermined interaction lists. The system self-determines which object the user wishes to interact with based on visual occlusion patterns.
Solution Approach 2:
The system changes the interaction parameter from predetermined object lists to dynamic optical occlusion detection. By monitoring changes in the visual field (occlusion parameters), the system adapts to any object the user is looking at, transforming the interaction model from static to dynamic.
2Adaptability or versatility
If the HMD uses optical occlusion detection to identify target objects, then the adaptability to various objects is improved, but the device complexity increases
Solution Approach 1:
The optical occlusion detection mechanism serves multiple functions: it identifies target objects, determines interaction intent, and enables flexible object selection. This single mechanism replaces the need for multiple separate systems (object recognition, gesture detection, manual selection interfaces).
Solution Approach 2:
The optical occlusion detection acts as an intermediary between the user's visual attention and the interaction system. Instead of directly analyzing complex object properties or requiring manual input, the system uses occlusion changes as a simple mediator to infer user intent and identify target objects.
3Measurement precision
If the HMD analyzes video to detect and identify objects, then the measurement precision of object detection is improved, but the processing time and energy consumption increase
Solution Approach 1:
The system extracts only the critical information needed for object identification - the optical occlusion changes in the visual field - rather than processing the entire video stream in detail. By focusing on occlusion patterns rather than complete object analysis, the system reduces processing requirements while maintaining identification accuracy.
Solution Approach 2:
The system performs partial analysis by detecting only the occlusion changes rather than complete object recognition. This partial action approach provides sufficient precision for identifying target objects without the computational overhead of full video analysis, reducing processing time and energy consumption.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables flexible interaction with various objects by accurately identifying target objects through changes in perceived characteristics, enhancing the functionality of wearable computing devices in real-world scenarios.
Implementation Method 1
the HMD detects a change to a perceived characteristic of the reference object and makes a determination that a detected object caused the change to the perceived characteristic
Data Source
AI summary
Methods are apparatuses are described for identifying a target object using optical occlusion. A head-mounted display perceives a characteristic of a reference object. The head-mounted display detects a change of the perceived characteristic of the reference object and makes a determination that a detected object caused the change of the perceived characteristic. In response to making the determination, the head-mounted display identifies the detected object as the target object.