PoseBias: On Dataset Bias and Task Difficulty - Is there an Optimal Camera Position for Facial Image Analysis?

Choithwani M, Almeida S, Egger B (2023)

Publication Language: English

Publication Type: Conference contribution

Publication year: 2023

Publisher: Institute of Electrical and Electronics Engineers Inc.

Pages Range: 3088-3096

Conference Proceedings Title: 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)

Event location: Paris FR

ISBN: 9798350307443

DOI: 10.1109/ICCVW60793.2023.00334

Open Access Link: https://openaccess.thecvf.com/content/ICCV2023W/AMFG/papers/Choithwani_PoseBias_On_Dataset_Bias_and_Task_Difficulty_-_Is_There_ICCVW_2023_paper.pdf

Abstract

Let's imagine you could choose the position of the camera for a particular face analysis task - where would you put it? In this work, we provide a first analysis based on synthetic training data to provide evidence that this choice is not trivial, not only dependent on the training data and different based on the task. We provide results for two major face analysis tasks, face recognition and landmark detection. For our experiments, we use a 3D Morphable Model as it provides us full control over pose, illumination, and identity to generate idealized training data. Whilst rendered images are not photorealistic we avoid any confounding factors and biases from other sources (e.g. pose bias in training data).Our results show that the optimal camera poses are near frontal but not exactly frontal and dependent on the task. By comparing the results obtained by pose-specific training set to a uniform training distribution without pose bias we show that the accuracy for both tasks not only depends on the bias in the training data but is actually dominated by the difficulty of the task depending on the particular pose.

Authors with CRIS profile

Sneha Almeida Professur für Cognitive Computer Vision (Stiftungsprofessur) Bernhard Egger Professur für Cognitive Computer Vision (Stiftungsprofessur)

How to cite

APA:

Choithwani, M., Almeida, S., & Egger, B. (2023). PoseBias: On Dataset Bias and Task Difficulty - Is there an Optimal Camera Position for Facial Image Analysis? In 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) (pp. 3088-3096). Paris, FR: Institute of Electrical and Electronics Engineers Inc..

MLA:

Choithwani, Mohit, Sneha Almeida, and Bernhard Egger. "PoseBias: On Dataset Bias and Task Difficulty - Is there an Optimal Camera Position for Facial Image Analysis?" Proceedings of the 2023 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2023, Paris Institute of Electrical and Electronics Engineers Inc., 2023. 3088-3096.

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