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Real-time Pupil Tracking from Monocular Video for Digital Puppetry

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arxiv 2006.11341 v1 pith:SAMZEZEE submitted 2020-06-19 cs.CV

Artsiom Ablavatski , Andrey Vakunov , Ivan Grishchenko , Karthik Raveendran , Matsvei Zhdanovich This is my paper · ORCID
classification cs.CV
keywords pupilreal-timeapproachtrackingvideoaccuratelyblendcoefficients
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We present a simple, real-time approach for pupil tracking from live video on mobile devices. Our method extends a state-of-the-art face mesh detector with two new components: a tiny neural network that predicts positions of the pupils in 2D, and a displacement-based estimation of the pupil blend shape coefficients. Our technique can be used to accurately control the pupil movements of a virtual puppet, and lends liveliness and energy to it. The proposed approach runs at over 50 FPS on modern phones, and enables its usage in any real-time puppeteering pipeline.

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  1. DOOMGAN:High-Fidelity Dynamic Identity Obfuscation Ocular Generative Morphing

    cs.CV 2025-07 conditional novelty 6.0 of 10

    DOOMGAN generates visible-spectrum ocular morphs that fool two ocular verification systems, with attack success rates above 90% at permissive thresholds and improved anatomical realism over prior morphing methods.

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