mlsanityData to 7 Oct 2026

Facial Landmark Detection Evaluation on MOBIO Database

arXiv 2307.03329 ↗First posted 6 Jul 2023cs.CVcited by 0

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Abstract (arXiv)

MOBIO is a bi-modal database that was captured almost exclusively on mobile phones. It aims to improve research into deploying biometric techniques to mobile devices. Research has been shown that face and speaker recognition can be performed in a mobile environment. Facial landmark localization aims at finding the coordinates of a set of pre-defined key points for 2D face images. A facial landmark usually has specific semantic meaning, e.g. nose tip or eye centre, which provides rich geometric information for other face analysis tasks such as face recognition, emotion estimation and 3D face reconstruction. Pretty much facial landmark detection methods adopt still face databases, such as 300W, AFW, AFLW, or COFW, for evaluation, but seldomly use mobile data. Our work is first to perform facial landmark detection evaluation on the mobile still data, i.e., face images from MOBIO database. About 20,600 face images have been extracted from this audio-visual database and manually labeled with 22 landmarks as the groundtruth. Several state-of-the-art facial landmark detection methods are adopted to evaluate their performance on these data. The result shows that the data from MOBIO database is pretty challenging. This database can be a new challenging one for facial landmark detection evaluation.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 16 of its 55 references that are in the map. First posted on arXiv 6 Jul 2023.

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References · 16

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  3. 2017SphereFace: Deep Hypersphere Embedding for Face Recognitioncited by 733
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  10. 2016Dynamic Attention-controlled Cascaded Shape Regression Exploiting Training Data Augmentation and Fuzzy-set Sample Weightingcited by 20
  11. 2015Facial Landmark Detection with Tweaked Convolutional Neural Networkscited by 13
  12. 2017Simultaneous Facial Landmark Detection, Pose and Deformation Estimation under Facial Occlusioncited by 12
4 more
  1. 2015Pose-Invariant 3D Face Alignmentcited by 8
  2. 2016Combining Data-driven and Model-driven Methods for Robust Facial Landmark Detectioncited by 8
  3. 2017Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wildcited by 7
  4. 2017Constrained Joint Cascade Regression Framework for Simultaneous Facial Action Unit Recognition and Facial Landmark Detectioncited by 3

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