Psychology-Driven Design of Intelligent Interfaces

T. Metin Sezgin introduces Intelligent User Interfaces Laboratory and their works on stuff that make interactions between human and computers and robots easier more natural and more intelligent.

Kart-ON

Our TUBITAK-funded project Kart-ON programming environment is designed as an affordable means to increase collaboration among students and decrease dependency on screen-based interfaces.  Kart-ON is a tangible programming language that uses everyday objects such as paper, pen, fabrics as programming objects and employs a mobile phone as the compiler.

Generation of 3D Human Models and Animations
Using Simple Sketches

We exploit Variational Autoencoders to develop a novel framework capable of transitioning from a simple 2D stick figure sketch, to a corresponding 3D human model. Our network learns the mapping between the input sketch and the output 3D model.

Video Super-Resolution Project

Video Super-Resolution aims to give a satisfying estimation of a high resolution image from multiple similar low resolution images.

Deep Stroke-based Sketched Symbol Reconstruction and Segmentation

We propose a neural network model that segments symbols into stroke-level components. Our segmentation framework has two main elements: a fixed feature extractor and a Multilayer Perceptron (MLP) network that identifies a component based on the feature

Can We Develeop Systems Having Human-like Perception?

T. Metin Sezgin introduces IUI Lab which aims humans and computers to communicate naturally. Generally, projects focus on interaction with robots, optimization of search engines, education and enhancements in workplace.

The ASC-Inclusion Perceptual Serious Gaming
Platform for Autistic Children

Often, individuals with an Autism Spectrum Condition (ASC) have difficulties in interpreting verbal and non-verbal communication cues during social interactions. We develop a platform for children who have an ASC to learn emotion expression and recognition, through play in the virtual world.

Identifying Visual Attributes for Object Recognition from Text and Taxonomy

Our evaluations demonstrate that both taxonomy and distributional similarity serve as useful sources of information for attribute nomination, and our methods can effectively exploit them.

HapTable

We develop a multi-modal interactive tabletop that allows users to interact with digital images and objects through natural touch gestures.

Generation of 3D Human Models and Animations
Using Simple Sketches

We demonstrate that our network can generate not only 3D models, but also 3D animations through interpolation and extrapolation in the learned embedding space. Extensive experiments show that our model learns to generate reasonable 3D models and animations

Identifying Visual Attributes for Object Recognition from Text and Taxonomy

Our evaluations demonstrate that both taxonomy and distributional similarity serve as useful sources of information for attribute nomination, and our methods can effectively exploit them.

We present a work-in-progress report on a sketch- and image-based software called ”CHER-ish” designed to help make sense of the cultural heritage data associated with sites within 3D space.

Audio-Facial Laughter Detection
in Naturalistic Dyadic Conversations

Our experiments show that our multimodal
approach supported by bagging compares favorably to the state of the art in presence of detrimental factors such as cross-talk,
environmental noise, and data imbalance.

Semantic Sketch-Based Video
Retrieval with Autocompletion

The system indexes collection data with over 30 visual features describing color,
edge, motion, and semantic information. Resulting feature data is stored in ADAM, an efficient database system
optimized for fast retrieval.

Systems are generally evaluated in terms of prediction accuracy, and on previously collected offline interaction data. Little attention has been paid to creating real-time interactive systems using eye gaze and evaluating them in online use. We have five main contributions that address this gap from a variety of aspects.

IMOTION – Searching for Video Sequences
Using Multi-Shot Sketch Queries

This paper presents the second version of the IMOTION
system, a sketch-based video retrieval engine supporting multiple query
paradigms. For the second version, the functionality and the usability of the system have been improved.

iAutoMotion – an Autonomous
Content-based Video Retrieval Engine

This paper introduces iAutoMotion, an autonomous video
retrieval system that requires only minimal user input. It is based on the
video retrieval engine IMOTION.

This paper presents a data collection of social interaction dialogs involving humor between a human participant and a robot. In this work, interaction scenarios have been designed in order to study social markers such as laughter.

Recent Developments and Results of ASC-Inclusion:
An Integrated Internet-Based Environment for Social
Inclusion of Children with Autism Spectrum Conditions

Individuals with Autism Spectrum Conditions (ASC) have marked difficulties using verbal and non-verbal communication for social interaction.  The ASC-Inclusion project helps children with ASC by allowing them to learn how emotions can be expressed and recognised via playing games in a virtual world.

HaptiStylus: A Novel Stylus Capable of Displaying
Movement and Rotational Torque Effects

We describe a novel stylus capable of displaying certain vibrotactile and inertial haptic effects to the user.  Oure xperimental results from our interactive pen-based game show that our haptic stylus is
effective in practical settings.

In this paper (1) an existing activity prediction system for pen-based devices is modified for real-time activity prediction and (2) an alternative time-based activity prediction system is introduced. Both systems use eye gaze movements that naturally accompany pen-based user interaction for activity classification.

Human-Computer Interaction

We can train a social robot via reinforcement learning so as to enhance user engagement by generating appropriate smiles, laughs and nodes during conversation

DPFrag: Trainable Stroke Fragmentation Based on Dynamic Programming

DPFrag is an efficient, globally optimal fragmentation method that learns segmentation parameters from data and produces fragmentations by combining primitive recognizers in a dynamic-programming framework. The fragmentation is fast and doesn’t require laborious and tedious parameter tuning. In experiments, it beat state-of-the-art methods on standard databases with only a handful of labeled examples.

Visualization Literacy

We work on understanding children’s visualization literacy to develop better interactive teaching material at elementary schools.

Active Learning for Sketch Recognition

Our results imply that the Margin based informativeness measure consistently outperforms other measures. We also show that active learning brings definitive advantages in challenging databases when accompanied with powerful feature representations.

Who Works at IUI Lab?

T. Metin Sezgin is explaining who works on IUI Lab and career opportunities waiting for students after graduation.

Human-Computer Interaction

We can train a social robot via reinforcement learning so as to enhance user engagement by generating appropriate smiles, laughs and nodes during conversation.

How Can Humans and Computers Communicate? 

 

Some information about Intelligent User Interfaces Laboratory and human-computer interaction.