I study interaction design in touchless systems—systems operated with freehand gestures—with a focus on developing intuitive interfaces for different considerations of use, such as interactive
visualization, collocated collaboration, or large display interaction.
Motor-Intuitive Interactions Based on Image
Schemas: Aligning Touchless Interaction Primitives with Human Sensorimotor Abilities
Chattopadhyay, D., & Bolchini, D.
Journal Paper Special
Issue on Intuitive Interactions, Interacting With Computers, 27(3), 327–343.
Touchless Circular Menus: Toward an Intuitive
UI for Touchless Interactions with Large Displays
Chattopadhyay, D., & Bolchini, D.
Conference Paper Proceedings of the International Working
Conference on Advanced Visual Interfaces, 33–40, ACM.
The long-term goal of this project is to identify critical social, communication and cognitive factors that can inform a fundamental rethinking of effective Drug-Drug Interaction alerts (DDI alerts) for physicians. Specifically, our objective is to uncover, demonstrate and evaluate novel principles for effective and novel alert design.
Understanding Advice Sharing among Physicians: Towards Trust-Based Clinical Alerts
Chattopadhyay, D., Rohani Ghahari, R., Duke, J., D., .& Bolchini, D.
Journal PaperInteracting with Computers, 28(4), 532–551.
Endorsement, Prior Action, and Language: Modeling Trusted Advice in Computerized Clinical Alerts
Chattopadhyay, D., Duke, J., D., & Bolchini, D.
Extended Abstract Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2016, 2027—2033, ACM.
The uncanny valley theory does not provide a causal explanation of why near-perfect human likeness of a stimulus elicits an eerie response. There is a debate on the extent to which the uncanny valley effect is a general cognitive phenomenon, or whether it involves visceral conflicts at the perceptual level. In this project, we are currently investigating if the eerie and cold feelings elicited by entities in the uncanny valley also involves specific affective biological adaptation, such as fear or threat avoidance.
Reducing consistency in human realism increases the uncanny valley effect; increasing category uncertainty does not
MacDorman, K., F., & Chattopadhyay, D.
Journal PaperCognition, 146, 190—205.
Familiar Faces Rendered Strange: Why Inconsistent Realism Drives Characters into the Uncanny Valley
In this project, we categorized human interactions using skeletal information. We created the K-10 Interaction dataset—ten different classes of two-person interactions performed among six different agents and recorded using the Kinect for Xbox 360. We represented human interactions in terms of local space-time features, aligned them using Canonical Time Warping, and used SVM and MILBoost for supervised classification.
Interaction Detection using Body-Pose Features and Multiple Instance Learning
Yun, K., Carrillo, J., H., Chattopadhyay, D., Berg, T., L., & Samaras, D.
Conference Paper Proceedings
of Computer Vision and Pattern Recognition Workshops, 28–35, IEEE.
Human Motion Initiated Music Generation using Skeletal Tracking by Kinect
Berg, T., L., Chattopadhyay, D., Schedel, M., & Vallier, T.
Conference Paper Proceedings of
Society for Electro-Acoustic Music in the United States, Wisconsin, USA.
Multimodal Tagging of Human Motion Using Skeletal Tracking With Kinect
Thesis & Dissertation Computer Science Department, State University of New York at Stony Brook.