Bag-of-Lies is a multi-modal dataset consisting of video, audio and eye gaze from 35 unique subjects collected using a carefully designed experiment for the task of automated deception detection (binary classification into truth/lie). It has a total of 325 manually annotated recordings consisting of 162 lies and 163 truths. Along with it, EEG (13 channels) data is also available for 22 unique subjects.
For the experiment, each subject was shown 6-10 select images and were asked to describe them deceptively or otherwise based on their choice. Video and Audio were captured using a standard phone camera and microphone, gaze data was collected using GazePoint GP3 Eye tracking system and EEG Data was captured using EPOC+ headset.
The database can be downloaded from the following link.
(6.14 GB) (CRC32: 8748CBD7, MD5: A18542168F2F178EBECAA292BFC791B3)
To obtain the password for the compressed file, email the duly filled license agreement
with the subject line "License agreement for Bag-of-Lies Database"
The license agreement has to be signed by someone having the legal authority to sign on behalf of the institute, such as the head of the institution or registrar. If a license agreement is signed by someone else, it will not be processed further.
This database is available only for research and educational purpose and not for any commercial use. If you use the database in any publications or reports:
- You must not use data from User_12 (as pictures or otherwise) in any publications / derived works using this dataset
- You must refer to the following papers:
- V. Gupta, M. Agarwal, M. Arora, T. Chakraborty, R. Singh, M. Vatsa. Bag-of-Lies: A Multimodal Dataset for Deception Detection, In IEEE Conference on Computer Vision and Pattern Recognition Workshop on Challenges and Opportunities for Privacy and Security, 2019.