University of Notre Dame Du Lac

Securiport LLC

Kevin Bowyer

Nathan Thomas Carpenter

Adam Czajka

Zhaoyuan Fang

Jeremy Speth

Leandro Olie

Patrick Flynn

The video based detection of pulse waveform includes systems, devices, methods, and computer-readable instructions for capturing a video stream including a sequence of frames, processing each frame of the video stream to spatially locate a region of interest, cropping each frame of the video stream to encapsulate the region of interest, processing the sequence of frames, by a 3-dimensional convolutional neural network, to determine the spatial and temporal dimensions of each frame of the sequence of frames and to produce a pulse waveform point for each frame of the sequence of frames, and generating a time series of pulse waveform points to generate the pulse waveform of the subject for the sequence of frames.

Video based detection of pulse waveform

Systems and methods for detecting textured contact lenses in an iris image are disclosed. Initially, 'K' images are taken of an eye in near-infrared light, each for a different positioning of the illuminant. Three-dimensional properties of the hypothetical iris are estimated based on image processing methods. The variability of the estimated three-dimensional properties is calculated, and a classification into two classes is made based on the variability. A low variability denotes that an authentic iris pattern was presented to the sensor, whereas a high variability denotes that the sensor observes an eye wearing a textured contact lens. The systems and methods disclosed allow for detecting presentation attacks to iris recognition systems/sensors based on presentation of an eye wearing a textured contact lens in an automatic and accurate way.

Method of textured contact lens detection

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South Bend, IN, United States of America

Kevin Bowyer