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Video-Based Deception Detection using Visual Cues

Author: Madhumitha Sivaraj
Lab: Computational Biomedicine Imaging and Modeling Center
Advisor: Dr. Dimitris Metaxas
Mentor: Anastasis Stathopoulos
Semester: Fall 2020

Corresponding paper can be found here. Slide deck can be found here.

Description

The act of deception is probably as old as civilization — not long after humans began communicating, they began communicating lies. Shortly after that, they probably started trying to force others to tell the truth. I built video-based deception detection models, training my task on a Resistance Game dataset. I developed three models (LSTM, GRU, TCN) with various aggregation techniques to accurately organize roles as deceptive and non-deceptive based on visual cues and robust facial features, such as raw pose, gaze, 1-D Facial Action Units.

Run

python3 main.py --model ['GRU','LSTM','TCN'] --aggregation ['last','average','max']

Run main.py file.

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CVML research at CBIM: Video-Based Deception Detection using Visual Cues

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