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Related Experiment Video

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Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

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Comparing Object Alignment Algorithms with Appearance Variation: Forward-Additive vs Inverse-Composition.

Patrick Lucey¹, Simon Lucey, Mark Cox

¹Speech, Audio, Image and Video Technology Laboratory, Queensland University of Technology, Brisbane, QLD, 4000, Australia.

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|September 28, 2011

Summary

This summary is machine-generated.

This study compares forward-additive (FA) and inverse-compositional (IC) algorithms for object alignment with appearance variations. FA offers greater refinement, proving a truer solution than IC in experiments.

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Area of Science:

Computer Vision
Image Processing
Machine Learning

Background:

Object alignment algorithms struggle with unseen intra-class appearance variations.
Gradient-descent variants like Lucas-Kanade (forward-additive, FA) and inverse-compositional (IC) algorithms attempt to solve alignment and appearance simultaneously.
Previous work showed FA and IC equivalence without appearance variation, with IC offering computational efficiency.

Purpose of the Study:

To compare the performance of FA and IC algorithms in the presence of appearance variation.
To investigate whether the computational benefits of IC over FA extend to scenarios with appearance variation.

Main Methods:

Conducted experiments comparing FA and IC algorithms on the MultiPIE face database.
Evaluated algorithm performance under conditions with intra-class appearance variation.

Main Results:

The FA and IC algorithms are not equivalent when appearance variation parameters are included.
The FA algorithm achieved greater refinement compared to the IC algorithm.
FA provides a truer solution than IC when dealing with appearance variations.

Conclusions:

The assumption of FA and IC equivalence does not hold with appearance variation.
The FA algorithm is superior to the IC algorithm for object alignment tasks involving appearance variations.
Future object alignment research should consider the distinct performance characteristics of FA and IC under appearance variation.