Smartphone Camera Object Selection via Motion Quiescence Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current smartphone camera technologies lack efficient interaction methods for users to select specific objects or scenes during photograph capture, leading to post-processing limitations and inefficiencies in capturing desired content.
Innovation Solution
A system that utilizes motion sensors and scene analysis to detect quiescence in the video stream, identifies preferred objects using heuristics and user preferences, and allows users to interactively select objects through gestures, eye-tracking, or screen inputs, presenting scenarios for final choice and capturing high-resolution shots of chosen objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If real-time object detection and selection is implemented, then user interaction capability during capture is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary object detection and scene analysis before the user finalizes their selection. Objects are identified and highlighted in advance, allowing users to make informed decisions about what to capture without needing complex real-time processing during the actual selection moment.
Solution Approach 2:
The patent introduces an intermediary layer between the camera and the user interface that processes video frames, detects objects, and presents simplified selection options to the user. This intermediary handles the computational complexity while presenting a simple, intuitive interaction model to the end user.
2Ease of operation
If multiple interaction modes (gestures, eye-tracking, screen inputs) are supported, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The system implements a universal interaction framework that can handle multiple input modalities (gestures, eye-tracking, screen touches) through a unified processing architecture. This allows the same core system to support diverse interaction methods without requiring separate dedicated systems for each mode.
Solution Approach 2:
The system automatically detects and highlights preferred objects based on predefined heuristics and user preferences, reducing the burden on users to manually search through complex scenes. The system serves itself by autonomously identifying capture targets, requiring minimal user input beyond simple confirmation or correction.
3Device complexity
If post-processing is used for object selection, then device complexity is reduced, but loss of time occurs
Solution Approach 1:
Object detection and scene analysis are performed in advance during the capture process itself, rather than waiting until after the photo is taken. This preliminary processing enables real-time highlighting and selection capabilities, eliminating the need for time-consuming post-processing while maintaining manageable system complexity through efficient algorithms.
Data Source
AI summary
Selecting objects in a video stream of a smart phone includes detecting quiescence of frame content in the video stream, detecting objects in a scene corresponding to the frame content, presenting at least one of the objects to a user of the smart phone, and selecting at least one of the objects in a group of objects in response to input by the user. Detecting quiescence of frame content in the video stream may include using motion sensors in the smart phone to determine an amount of movement of the smart phone. Detecting quiescence of frame content in the video stream may include detecting changes in view angles and distances of the smart phone with respect to the scene. Detecting objects in a scene may use heuristics, custom user preferences, and/or specifics of scene layout. At least one of the objects may be a person or a document.