CCTV Monitoring Task in Surveillance Scenario with Multi-human Multi-robot Team
CCTV Monitoring Task in Surveillance Scenario with Multi-human Multi-robot Team
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In the interest of better mimicking real-world workload scenarios, we proposed a CCTV monitoring task scenario, in which human operators monitor and control a display interface (or multiple interfaces simultaneously).
Potential scenarios of surveillance missions with MH-MR system
Security monitoring (e.g., NASA, Jail, CCTV center, etc.)
Air traffic management
and performance checking
in which human operators undertake a simultaneous CCTV monitoring task while multiple sensors track them.
During the task, the participant was asked to observe the webcam streams captured by the robots
The camera views are streamed on the CCTV Monitoring Task GUI program.
Participants were asked to monitor and detect two types of objects:
(a) abnormal objects (including skeleton); Earn +1 point (reward)
(b) normal objects (AmongUS); lose -3 point (penality)
Supplementary Videos
Supplementary Videos
The CCTV monitoring task was used as a stimulus to collect a multimodal dataset having physiological and behavioral features [1].
If you are interested in our dataset, please visit this link: https://polytechnic.purdue.edu/ahmrs/mocas-dataset
Opensource CCTV monitoring tasks GUI program to evoke the targeted affecitve loads (e.g., low, medium, and high levels) [2].
If you are interested in the GUI program, please visit this link: https://github.com/SMARTlab-Purdue/SMART-TeleLoad
References
References
[1] Wonse Jo*, Ruiqi Wang*, Go-Eum Cha, Su Sun, Revanth Senthilkumaran, Daniel Foti, and Byung-Cheol Min (* equal contribution), "MOCAS: A Multimodal Dataset for Objective Cognitive Workload Assessment on Simultaneous Tasks", IEEE Transactions on Affective Computing, Early Access, 2024. (PDF, Video)
[2] Wonse Jo, Go-Eum Cha, Dan Foti, and Byung-Cheol Min, "SMART-TeleLoad: A New Graphic User Interface to Generate Affective Loads for Teleoperation", SoftwareX, Vol. 26, 101757, May 2024. (PDF, Video, GitHub) )
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