# Deception Detection and Remote Physiological Monitoring: A Dataset and Baseline Experimental Results

arXiv: https://arxiv.org/abs/2106.06583 · HTML: https://mlsanity.com/paper/2106.06583/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 44 references that are in the map.
- First posted on arXiv 11 Jun 2021.

## Builds on (most cited first, 6 of 6)

- [Remote Photoplethysmograph Signal Measurement from Facial Videos Using Spatio-Temporal Networks](https://mlsanity.com/paper/1905.02419/) (2019)
- [VIPL-HR: A Multi-modal Database for Pulse Estimation from Less-constrained Face Video](https://mlsanity.com/paper/1810.04927/) (2018)
- [A Reproducible Study on Remote Heart Rate Measurement](https://mlsanity.com/paper/1709.00962/) (2017)
- [SAMM Long Videos: A Spontaneous Facial Micro- and Macro-Expressions Dataset](https://mlsanity.com/paper/1911.01519/) (2019)
- [Analysis of CNN-based remote-PPG to understand limitations and sensitivities](https://mlsanity.com/paper/1911.02736/) (2019)
- [Spotting Macro- and Micro-expression Intervals in Long Video Sequences](https://mlsanity.com/paper/1912.11985/) (2019)

## Built on by (most cited first, 16 of 16)

- [Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal Learning](https://mlsanity.com/paper/2303.12745/) (2023)
- [Advancing Generalizable Remote Physiological Measurement through the Integration of Explicit and Implicit Prior Knowledge](https://mlsanity.com/paper/2403.06947/) (2024)
- [A Survey on Infrared Image and Video Sets](https://mlsanity.com/paper/2203.08581/) (2022)
- [Full-Body Cardiovascular Sensing with Remote Photoplethysmography](https://mlsanity.com/paper/2303.09638/) (2023)
- [MSPM: A Multi-Site Physiological Monitoring Dataset for Remote Pulse, Respiration, and Blood Pressure Estimation](https://mlsanity.com/paper/2402.02224/) (2024)
- [Can Deception Detection Go Deeper? Dataset, Evaluation, and Benchmark for Deception Reasoning](https://mlsanity.com/paper/2402.11432/) (2024)
- [Digital and Physical-World Attacks on Remote Pulse Detection](https://mlsanity.com/paper/2110.11525/) (2021)
- [EyePreserve: Identity-Preserving Iris Synthesis](https://mlsanity.com/paper/2312.12028/) (2023)
- [Promoting Generalization in Cross-Dataset Remote Photoplethysmography](https://mlsanity.com/paper/2305.15199/) (2023)
- [Measuring Domain Shifts using Deep Learning Remote Photoplethysmography Model Similarity](https://mlsanity.com/paper/2404.08184/) (2024)
- [SiNC+: Adaptive Camera-Based Vitals with Unsupervised Learning of Periodic Signals](https://mlsanity.com/paper/2404.13449/) (2024)
- [Hallucinated Heartbeats: Anomaly-Aware Remote Pulse Estimation](https://mlsanity.com/paper/2303.06452/) (2023)
- [Refining Remote Photoplethysmography Architectures using CKA and Empirical Methods](https://mlsanity.com/paper/2401.04801/) (2024)
- [Dynamic Emotion and Personality Profiling for Multimodal Deception Detection](https://mlsanity.com/paper/2604.17037/) (2026)
- [Exploring Remote Physiological Signal Measurement under Dynamic Lighting Conditions at Night: Dataset, Experiment, and Analysis](https://mlsanity.com/paper/2507.04306/) (2025)
- [DecepGPT: Schema-Driven Deception Detection with Multicultural Datasets and Robust Multimodal Learning](https://mlsanity.com/paper/2603.23916/) (2026)

## Abstract (arXiv)

We present the Deception Detection and Physiological Monitoring (DDPM) dataset and initial baseline results on this dataset. Our application context is an interview scenario in which the interviewee attempts to deceive the interviewer on selected responses. The interviewee is recorded in RGB, near-infrared, and long-wave infrared, along with cardiac pulse, blood oxygenation, and audio. After collection, data were annotated for interviewer/interviewee, curated, ground-truthed, and organized into train / test parts for a set of canonical deception detection experiments. Baseline experiments found random accuracy for micro-expressions as an indicator of deception, but that saccades can give a statistically significant response. We also estimated subject heart rates from face videos (remotely) with a mean absolute error as low as 3.16 bpm. The database contains almost 13 hours of recordings of 70 subjects, and over 8 million visible-light, near-infrared, and thermal video frames, along with appropriate meta, audio and pulse oximeter data. To our knowledge, this is the only collection offering recordings of five modalities in an interview scenario that can be used in both deception detection and remote photoplethysmography research.