NDLI: Real time feature point tracking with automatic model selection

Content Provider	IEEE Xplore Digital Library
Author	Ionita, M.C. Tresadern, P.A. Cootes, T.F.
Copyright Year	2011
Description	Author affiliation: Imaging Science and Biomedical Engineering, University of Manchester, M13 9PT, United Kingdom (Ionita, M.C.; Tresadern, P.A.; Cootes, T.F.)
Abstract	We present an efficient and accurate algorithm for face tracking using a set of Active Appearance Models (AAMs). We observe that a single AAM, trained at a particular model resolution and a particular range of displacements, has a “sweet spot” - a range of displacements for which it is most accurate. A common approach to increasing the range of convergence is to use a multi-resolution model, or a sequence of AAMs trained on smaller and smaller displacements. However, during tracking it is inefficient to run the whole sequence at every frame. If there has been little movement since the previous frame, it is sufficient to only run one step of a single higher resolution AAM. In this paper we show that we can use a non-linear regressor to estimate the magnitude of the displacement from the optimal position in the current frame, and use this to select a model which has been tuned to work well at that displacement. This is significantly more efficient than running a complete sequence of models at every frame. We describe the method in detail and demonstrate its performance on several datasets.
Starting Page	453
Ending Page	460
File Size	1355846
Page Count	8
File Format	PDF
ISBN	9781467300629
e-ISBN	9781467300636
DOI	10.1109/ICCVW.2011.6130276
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-06
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Adaptation models Shape Tracking Biological system modeling Active appearance model Face
Content Type	Text
Resource Type	Article

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