Time-lapse Image Retention via Conditional Filtering
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Solution Overview
Problem
Time-lapse photography generates excessive image data, leading to inefficient storage and retrieval of meaningful images, particularly when recording over extended periods, due to repetitive data and high power consumption.
Innovation Solution
An electronic device with an image-capturing function determines whether captured images meet specific retention criteria, such as brightness or face recognition, to decide whether to store them, thereby reducing storage space and improving data efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If time-lapse photography is performed for extended periods to record more images, then the coverage of recorded content is improved, but the storage space occupied increases significantly
Solution Approach 1:
The patent changes the parameter of image retention by introducing conditional criteria (brightness threshold, face detection, motion detection) to determine whether to store each captured image. This selective retention based on multiple parameters reduces storage space while maintaining recording duration.
Solution Approach 2:
The patent extracts and removes redundant or low-value images from the stored dataset by applying filtering conditions. Only images meeting specific criteria (sufficient brightness, containing faces, or showing motion) are retained, while others are discarded to reduce storage occupation.
2Loss of information
If all captured images are stored to ensure no meaningful content is lost, then the completeness of recorded information is improved, but the time required to screen and find meaningful images increases
Solution Approach 1:
The patent performs preliminary screening of captured images immediately after acquisition by evaluating brightness, face presence, and motion detection. This preliminary action filters out non-meaningful images before storage, so users only need to review stored images that have already been pre-screened for potential value.
Solution Approach 2:
The system provides feedback to users about which images are stored and why (based on detected features like faces or motion), enabling efficient retrieval without manual screening of all captured images. Users can search stored images using keywords or time ranges with confidence that meaningful content is included.
3Measurement precision
If image capture frequency is increased to capture more details, then the detail richness of recorded content is improved, but the power consumption increases
Solution Approach 1:
The patent implements dynamic adjustment of capture frequency based on scene conditions. When motion is detected or important events occur (indicated by brightness changes or face detection), the capture frequency increases to record details. During static periods, frequency decreases to conserve power, creating a dynamic balance between detail richness and energy consumption.
4Productivity
If conditional filtering is applied to reduce stored images, then the storage efficiency is improved, but the complexity of the image processing system increases
Solution Approach 1:
The patent segments the image filtering process into multiple independent modules: brightness evaluation, face detection, and motion detection. Each module operates independently and contributes to the overall retention decision, making the complex processing system organized and manageable while achieving high storage efficiency.
Data Source
AI summary
A time-lapse photography method includes several steps as follows. A determination is immediately made as to whether an image retaining condition is satisfied whenever an electronic device with an image-capturing function collects at least one data set. The data set includes a captured image. When the image retaining condition is satisfied, the captured image of the data set is stored; otherwise, the captured image of the data set is refused to be stored.