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Article Dans Une Revue Image and Vision Computing Année : 2020

Implementing Cascade of Regression-based Face Landmarking: an in-Depth Overview

Résumé

Face landmarking, defined as the detection of fiducial points on faces, has received a lot of attention over the last two decades within the computer vision community. While research literature documents major advances using state-of-art deep convolutional neural networks, earlier cascaded regression tree-based approaches remain a relevant alternative for low-cost, low-power embedded systems. Yet, from a practical point of view, their implementation and parametrization can be a difficult and tedious process. In this paper, we provide the readers with insights and advice on how to design a successful face landmarking system using a cascade of regression trees.
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Dates et versions

hal-02884592 , version 1 (07-09-2020)

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Romuald Perrot, Pascal Bourdon, David Helbert. Implementing Cascade of Regression-based Face Landmarking: an in-Depth Overview. Image and Vision Computing, 2020, 102, pp.103976. ⟨10.1016/j.imavis.2020.103976⟩. ⟨hal-02884592⟩
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