Object-Aware Timelapse Capture for User Activity Replay
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Solution Overview
Problem
Existing systems fail to selectively capture and replay user-based activities in computer-generated environments, particularly in extended reality settings, by identifying and prioritizing relevant objects based on user interaction and preferences.
Innovation Solution
An electronic device with integrated sensors and cameras captures images for formulating a timelapse of user activities, activating an image compilation mode to detect user gaze and object interest, and generating events based on predefined criteria such as gaze duration and user data, to create a compilation of images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system captures all objects in the physical environment during user activities, then the completeness of the timelapse compilation is improved, but the device complexity and data processing requirements increase significantly
Solution Approach 1:
The system extracts only the relevant objects that meet predefined criteria from the entire physical environment during user activities. Instead of capturing all objects, the system selectively identifies and captures only those objects that satisfy specific conditions (e.g., user gaze duration, object importance), thereby reducing data volume and processing complexity while maintaining compilation completeness.
Solution Approach 2:
The system applies different capture strategies to different regions and objects based on their relevance to the user activity. High-priority objects that meet criteria are captured with higher frequency and detail, while less relevant objects are either captured minimally or not at all. This localized quality approach optimizes resource allocation and reduces overall system complexity.
2Device complexity
If the system selectively captures only objects meeting predefined criteria, then the device complexity is reduced, but the measurement precision of user interest detection must be improved
Solution Approach 1:
The system implements feedback mechanisms that continuously monitor user interactions and adjust capture criteria in real-time. By analyzing user gaze patterns, interaction history, and behavioral data, the system refines its detection algorithms to accurately identify objects of interest. This feedback loop improves measurement precision without requiring proportionally increased device complexity, as the system learns and adapts from user behavior.
Solution Approach 2:
The system performs preliminary analysis of user preferences, historical data, and contextual information before the actual capture process. By pre-processing and pre-classifying potential objects of interest based on available user data, the system reduces the real-time processing burden and improves detection precision through informed decision-making about which objects to capture.
3Productivity
If the system captures images continuously during user activities, then the productivity of timelapse generation is improved, but the energy consumption increases
Solution Approach 1:
Instead of continuous capture, the system employs periodic capture at strategically determined intervals. Capture events are triggered by specific conditions such as user interactions, gaze duration thresholds, or significant environmental changes. This periodic approach maintains timelapse generation productivity by capturing key moments while dramatically reducing energy consumption compared to uninterrupted continuous capture.
Solution Approach 2:
The system autonomously manages its own capture operations by automatically detecting when capture is necessary based on predefined criteria and user behavior patterns. The system self-regulates capture frequency and intensity without requiring constant user input or manual configuration, optimizing the balance between productivity and energy consumption through intelligent, context-aware decision-making.
Data Source
AI summary
In some examples, an electronic device detects initiation of an exercise activity associated with a user of the electronic device. In some examples, in response to detecting the initiation of the exercise activity, the electronic device activates an image compilation capture mode of operation in which one or more images for formulating a compilation of the one or more images corresponding to the exercise activity are captured, including capturing one or more portions of a physical environment. In some examples, while the image compilation capture mode of operation is active, the electronic device visually detects a first object in the one or more captured portions of the physical environment. In some examples, in accordance with a determination that the first object satisfies one or more criteria, the electronic device generates a first event associated with formulating a first compilation of one or more images corresponding to the exercise activity.