Flipbook Production Through Quality-Aware Video Frame Selection
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Solution Overview
Problem
Existing systems for producing flipbooks from videos lack efficient video and image analysis capabilities, resulting in the selection and production of frames that are not of sufficient quality and desirability for printing.
Innovation Solution
A system and method that utilizes processing circuitry to select high-quality frames from a video by determining an average rate of change and a threshold of relative image difference, allowing for the selection of frames that meet quality criteria and arranging them in temporal order for printing and binding, with optional machine learning and user input for frame selection and editing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing systems extract frames from video to create flipbooks, then the flipbook can be produced, but the frame quality and desirability for printing are insufficient
Solution Approach 1:
The system performs preliminary video analysis before frame extraction to identify segments containing subjects of interest. By pre-analyzing the video to determine start and end frames of subject segments, the system ensures that only relevant high-quality frames are selected for the flipbook, improving frame quality while managing complexity through staged processing.
Solution Approach 2:
The patent replaces simple mechanical frame extraction with sophisticated image processing and machine learning algorithms. The system uses pixel-by-pixel comparison, variance calculation, and neural network-based subject identification to automatically select frames meeting quality criteria, substituting automated intelligent systems for manual or simple automated extraction methods.
2Productivity
If more frames are selected from video, then the flipbook captures more action, but the quality criteria may not be met by all selected frames
Solution Approach 1:
The system implements feedback mechanisms where selected frames are evaluated against multiple quality criteria including subject presence, image clarity, and action relevance. Frames that fail to meet criteria are rejected and the system adjusts selection parameters, using variance calculations and comparative analysis to iteratively improve frame selection quality while maintaining productivity.
Solution Approach 2:
The patent dynamically adjusts selection parameters such as frame rate, quality thresholds, and segment duration based on video content analysis. By changing parameters like the minimum variance threshold for subject detection or the frame sampling rate within segments, the system optimizes both the quantity of frames selected and their overall quality for the flipbook.
Data Source
AI summary
A system for producing a flipbook includes a processor that receives a video comprising a plurality of frames, selects a start frame and an end frame, and a plurality of frames therebetween. The processor can analyze the frames of the segment to determine an average rate of change of the plurality of frames and a threshold of relative image difference based on the average rate of change of the plurality of frames and a baseline frame rate. The processor can select, based on the results of its analysis, a plurality of selected frames, each of the selected frames being separated from two other selected frames by a sub-segment of the video, wherein each pair of adjacent frames comprises a relative image difference above the threshold and wherein each selected frame meets quality criteria not met by one or more local frames. The processor arranges the selected frames in temporal order, adds a protruding edge to each of the selected frames, and transmits data representing each of the selected frames to a printer for printing and binding a flipbook.