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We are interested in enabling natural human-computer interaction by combining techniques from machine learning, computer vision, computer graphics, human-computer interaction and psychology. Specific areas that we focus on include: multimodal human-computer interfaces, affective computing, pen-based interfaces, sketch-based applications, intelligent user interfaces, applications of computer vision and machine learning to solving real world problems. Browse through the publications and research pages to get a flavor of IUI@Koc.

The ASC-Inclusion Perceptual Serious Gaming Platform for Autistic Children
‘Serious games’ are becoming extremely relevant to individuals who have specific needs, such as children with an Autism Spectrum Condition
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HapTable: An Interactive Tabletop Providing Online Haptic Feedback for Touch Gestures
We present HapTable; a multi–modal interactive tabletop that allows users to interact with digital images and objects through natural touch
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Audio-Visual Prediction of Head-Nod and Turn-Taking Events in Dyadic Interactions
Head-nods and turn-taking both significantly contribute conversational dynamics in dyadic interactions. Timely prediction and use of these events is quite
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Multifaceted Engagement in Social Interaction with a Machine: the JOKER Project
This paper addresses the problem of evaluating engagement of the human participant by combining verbal and nonverbal behaviour along with
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Gaze-based predictive user interfaces: Visualizing user intentions in the presence of uncertainty
Human eyes exhibit different characteristic patterns during different virtual interaction tasks such as moving a window, scrolling a piece of
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Visualization Literacy at Elementary School
This work advances our understanding of children’s visualization literacy, and aims to improve it with a novel approach for teaching
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CHER-ish: A sketch- and image-based system for 3D representation and documentation of cultural heritage sites
We present a work-in-progress report on a sketch- and image-based software called “CHER-ish” designed to help make sense of the
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Audio-Facial Laughter Detection in Naturalistic Dyadic Conversations
We address the problem of continuous laughter detection over audio-facial input streams obtained from naturalistic dyadic conversations. We first present
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Computers & Graphics
Sketch recognition is the task of converting hand-drawn digital ink into symbolic computer representations. Since the early days of sketch
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Characterizing User Behavior for Speech and Sketch-based Video Retrieval Interfaces
From a user interaction perspective, speech and sketching make a good couple for describing motion. Speech allows easy specification of
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