244 citations · 311 across the 6 of their papers we have counts for
6 papers
VitalLens 2.0: High-Fidelity rPPG for Heart Rate Variability Estimation from Face Video
Philipp V. Rouast
This report introduces VitalLens 2.0, a new deep learning model for estimating physiological signals from face video. This new model demonstrates a significant leap in accuracy for…
VitalLens: Take A Vital Selfie
Philipp V. Rouast
This report introduces VitalLens, an app that estimates vital signs such as heart rate and respiration rate from selfie video in real time. VitalLens uses a computer vision model t…
Single-stage intake gesture detection using CTC loss and extended prefix beam search
Philipp V. Rouast, Marc T. P. Adam
Accurate detection of individual intake gestures is a key step towards automatic dietary monitoring. Both inertial sensor data of wrist movements and video data depicting the upper…
OREBA: A Dataset for Objectively Recognizing Eating Behaviour and Associated Intake
Philipp V. Rouast, Hamid Heydarian, Marc T. P. Adam +1
Automatic detection of intake gestures is a key element of automatic dietary monitoring. Several types of sensors, including inertial measurement units (IMU) and video cameras, hav…
Learning deep representations for video-based intake gesture detection
Philipp V. Rouast, Marc T. P. Adam
Automatic detection of individual intake gestures during eating occasions has the potential to improve dietary monitoring and support dietary recommendations. Existing studies typi…
Deep Learning for Human Affect Recognition: Insights and New Developments
Philipp V. Rouast, Marc T. P. Adam, Raymond Chiong
Automatic human affect recognition is a key step towards more natural human-computer interaction. Recent trends include recognition in the wild using a fusion of audiovisual and ph…