rPPG
Definition
Remote photoplethysmography. A technique for measuring heart rate from subtle periodic colour changes in facial skin caused by blood-volume pulses. Authentic video shows coherent rPPG signals; synthesised faces typically do not.
- Full name
- Remote photoplethysmography
- Signal source
- Skin colour changes from blood-volume pulses
- Use in detection
- Checks for coherent physiological pulse in video
- Application
- Deepfake and synthetic-face video detection
Common questions
Why does rPPG expose deepfakes?+
Real facial video carries a faint periodic colour signal from the heartbeat pumping blood through skin capillaries. Most face-generation models do not reproduce this physiological pattern, so a synthesised face often shows a weak, absent, or inconsistent rPPG signal across regions that should pulse in sync.
Can rPPG be fooled by newer generative models?+
Yes. As detection methods that rely on rPPG became known, some generation pipelines began adding synthetic pulsatile colour variation to defeat this check, so rPPG is used alongside other signal and semantic cues rather than as a standalone test.
Does rPPG require special hardware?+
No. It is extracted computationally from ordinary RGB video by tracking subtle colour changes over time in facial regions, which is what makes it useful for after-the-fact analysis of video files rather than only live capture.
Related terms
- CLIP-Based Detection
- Detection approach using OpenAI CLIP or similar vision-language foundation models as a feature extractor. The broad pre-training enables generalisation to generation methods...
- CNN Residual Detector
- A convolutional neural network trained on the high-frequency residual image, the difference between the original and a de-noised version, to classify whether...
- Detection Generalisation
- The capacity of a trained detector to correctly identify deepfakes produced by generators not seen during training. Low generalisation is the central...
- FaceForensics++
- A video dataset released by Rossler et al. (2019) containing 1000+ YouTube videos manipulated by four methods: DeepFakes, Face2Face, FaceSwap, and NeuralTextures....
- Frequency-Domain Analysis
- Detection approach that transforms image patches into the frequency domain (DCT or FFT) to expose periodic artifacts introduced by upsampling layers in...
- Frequency-Domain Artefact
- A periodic or statistical anomaly in the Fourier spectrum of an image or audio signal introduced by the generation pipeline's upsampling, filter,...
- Generalisation Gap
- The drop in detection accuracy when a classifier trained on one generation method is applied to a different method. Caused by learning...
- Noiseprint
- A CNN-based camera-model fingerprint extractor by Cozzolino and Verdoliva. Applied to deepfakes, it reveals inconsistency between the camera fingerprint in the genuine...
- Physiological Signal
- A biological process visible in video, such as eye blinking, rPPG (remote photoplethysmography), and head micro-motion from the cardiac cycle, that deepfake...
- Remote Photoplethysmography (rPPG)
- A technique that detects the pulse-driven skin-colour variation in a face video without contact sensors. In real video, this signal is present...
- XceptionNet
- A depthwise-separable convolutional architecture proposed by Rossler et al. as the baseline binary classifier in FaceForensics++. Trained to distinguish real from manipulated...