Camera-Statistics Frame Selection for Faster Video AI Processing

Solution Overview

Problem

Conventional media processing applications are inefficient and resource-intensive, particularly when handling high-quality video data, leading to excessive processing power consumption and time requirements.

Innovation Solution

A statistics-based video pre-processing system that analyzes camera statistics from video capturing devices to selectively identify and provide a subset of image frames to an image processing model, optimizing resource usage and enhancing accuracy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If conventional media processing applications process all image frames from high-quality video, then processing completeness is improved, but processing time and resource consumption increase significantly

Engineering Contradiction:

Improveprocessing completenessVSAvoidprocessing time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The system performs preliminary analysis of camera statistics (exposure, focus, white balance) before full image processing to identify frames that meet quality thresholds, pre-filtering out frames that would be wasted processing resources

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system applies partial processing by only fully processing frames that meet camera statistic criteria, while performing lighter processing or skipping frames that do not meet the criteria, achieving sufficient processing completeness without excessive resource expenditure

Inventive Principle:

Principle #16Partial or excessive action

2Manufacturing precision

If conventional media processing applications process all image frames from high-quality video, then processing completeness is improved, but computing power consumption increases significantly

Engineering Contradiction:

Improveprocessing completenessVSAvoidprocessing power

Core Design Contradiction:

Manufacturing precisionVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary analysis of camera statistics (exposure, focus, white balance) before full image processing to identify frames that meet quality thresholds, pre-filtering out frames that would be wasted processing resources

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system applies partial processing by only fully processing frames that meet camera statistic criteria, while performing lighter processing or skipping frames that do not meet the criteria, achieving sufficient processing completeness without excessive resource expenditure

Inventive Principle:

Principle #16Partial or excessive action

3Measurement precision

If camera statistics are analyzed for each frame, then processing accuracy is improved, but processing speed decreases

Engineering Contradiction:

Improveprocessing accuracyVSAvoidprocessing speed

Core Design Contradiction:

Measurement precisionVSSpeed

Solution Approach 1:

The system performs camera statistic analysis selectively on a subset of frames (e.g., at reduced frame rate or only on keyframes) rather than every frame, achieving sufficient processing accuracy for quality assessment without the full speed penalty of analyzing every single frame

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system applies different processing rigor to different frames based on local characteristics identified by camera statistics, performing detailed analysis only where needed and using simplified assessment for other frames

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS12602927B2Pre-processing image frames based on camera statistics

Publication Date: 2026.04.14 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

The present disclosure relates to systems, methods, and computer-readable media for selectively identifying image frames from an input video to provide to an image processing model based on camera statistics. For example, systems disclosed herein include receiving an input video and associated camera statistics from a video capturing device. The systems disclosed herein further include identifying select image frames to provide to the image processing model based on the camera statistics and based on an application of the image processing model. The systems disclosed herein further include selectively identifying and providing camera statistics to the image processing model. By selectively providing data to the image processing model based on camera statistics, the systems disclosed herein can leverage capabilities of video capturing devices to significantly reduce the expense of processing resources when utilizing a variety of image processing models.