Camera User-Intent Detection for Automatic Video or Image Capture
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Electronic devices with sophisticated camera capabilities face challenges in user interface design, making it difficult for users to quickly select the correct tools and functionality for capturing specific moments, often resulting in missed opportunities or suboptimal captures.
Innovation Solution
A machine learning system that analyzes motion, position, and image data to determine user intent for video or image capture, automatically adjusting the camera mode without manual user interaction, and saving both options for later selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the camera provides multiple shooting modes and options, then the camera capabilities are enhanced, but the user interface becomes increasingly difficult to operate and users may miss capturing moments
Solution Approach 1:
The camera system automatically detects user intent through sensor data analysis and machine learning models, enabling the camera to select appropriate shooting modes without manual user input. The system serves itself by interpreting motion patterns, device orientation, and environmental context to determine whether the user intends to capture images or record videos
Solution Approach 2:
The system performs preliminary analysis of sensor information and extracts features before the user actually captures a moment. By pre-processing motion data, position data, and image data to predict user intent, the system prepares the appropriate shooting mode in advance, eliminating the need for users to manually switch modes at the critical moment
2Measurement precision
If users manually select shooting modes, then the correct tools can be applied, but the specific moments may pass without capture due to review time
Solution Approach 1:
The system continuously monitors sensor data including motion sensors, position sensors, and imaging sensors to provide real-time feedback about user behavior patterns. This feedback loop allows the machine learning model to dynamically adjust and improve its prediction of user intent, enabling accurate mode selection without requiring users to spend time reviewing options
Solution Approach 2:
The patent replaces the mechanical interaction of manual mode selection with an automated sensing and detection system. Instead of users physically navigating through mode options, the system uses machine learning models to detect user intent from sensor data and automatically configure the appropriate shooting mode, substituting physical manipulation with intelligent automation
Data Source
AI summary
A method includes, in response to initiating a shooting mode of a camera application on an electronic device, collecting sensor information comprising at least one of: motion data of the electronic device, position data of the electronic device, and image data captured by one or more imaging sensors of the electronic device, wherein the shooting mode represents at least one of: a video record mode and an image capture mode. The method also includes determining, using a trained machine learning model, whether a user intention is to record video or capture an image based on features extracted from the sensor information. The method further includes recording video regardless of the shooting mode in response to determining that the user intention is to record video or capturing the image regardless of the shooting mode in response to determining that the user intention is to capture the image.