Fast Rotation Estimation Using Integral Projections

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Solution Overview

Problem

Existing methods for estimating rotational variations between consecutive video frames or image pairs are resource-intensive and computationally expensive, making real-time image rotation and panorama creation challenging.

Innovation Solution

The method involves determining frame-to-frame rotation by calculating global XY alignments and delta-X, delta-Y differences between matching corner regions, using integral projection vectors, and convoluting these vectors with variable and fixed length vectors to estimate rotation efficiently, reducing computational complexity and enabling fast rotation estimation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If high accuracy rotation estimation and image resampling are used before stitching, then panorama creation quality is improved, but computational cost and memory requirements increase significantly

Engineering Contradiction:

Improverotation estimation accuracyVSAvoidcomputational complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the image into multiple regions (e.g., four corner regions) and performs rotation estimation independently on each segment using integral projection vectors. This divides the computationally intensive global rotation estimation into smaller, manageable local estimations, reducing overall computational complexity while maintaining accuracy through aggregation of local results.

Inventive Principle:

Principle #1Segmentation

2Measurement precision

If image resampling is performed to compensate for rotation, then image alignment accuracy is improved, but processing time increases making real-time operation difficult

Engineering Contradiction:

Improveimage alignment accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent performs preliminary rotation estimation using integral projection vectors on segmented image regions before actual image stitching. By pre-calculating rotation parameters from simplified projections rather than full image resampling, the system prepares alignment data in advance, enabling faster subsequent stitching operations and real-time performance.

Inventive Principle:

Principle #10Preliminary action

3Reliability

If traditional rotation estimation methods are used, then rotation detection capability is maintained, but resource consumption increases

Engineering Contradiction:

Improverotation detection capabilityVSAvoidcomputational resource consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent extracts only the essential features needed for rotation estimation by computing integral projection vectors from segmented image regions. Instead of processing entire images with complex rotation algorithms, it extracts and processes only the projection data from key regions, significantly reducing computational resource consumption while preserving rotation detection capability.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS8587665B2Fast rotation estimation of objects in sequences of acquired digital images

Publication Date: 2013.11.19 ADEIA IMAGING LLC

AI summary

A measure of frame-to-frame rotation is determined. A global XY alignment of a pair of frames is performed. Local XY alignments in at least two matching corner regions of the pair of images are determined after the global XY alignment. Based on differences between the local XY alignments, a global rotation is determined between the pair of frames.