Ioannis Gkioulekas

I am a 5th year PhD candidate in the School of Engineering and Applied Sciences at Harvard University. My advisor is Todd Zickler.

Before coming to Harvard, I received a Diploma (five-year degree) in Electrical and Computer Engineering from the National Technical University of Athens, Greece, where I worked with Petros Maragos.

email | CV | LinkedIn | google scholar | contact

that's me
Research Interests

I'm interested in computer vision, machine-learning, and computer graphics. I am particularly interested in the appearance of materials in images: how we perceive it, how we can model it, how we can measure it, how we can find it, and how we can use it to tell something about the world the images represent.


Publications
acquisition

Inverse Volume Rendering with Material Dictionaries
Ioannis Gkioulekas, Shuang Zhao, Kavita Bala, Todd Zickler, Anat Levin
ACM Transactions on Graphics 2013 (SIGGRAPH Asia 2013)
paper | project page

We present a system for measuring the bulk scattering properties of a homogeneous volumetric material sample. The proposed system can be used for both solid and liquid materials and does not restrict the shape of the phase function.

translucency

Understanding the Role of Phase Function in Translucent Appearance
Ioannis Gkioulekas, Bei Xiao, Shuang Zhao, Edward H. Adelson, Todd Zickler, Kavita Bala
ACM Transactions on Graphics 2013 (Presented at SIGGRAPH 2013)
paper | project page

We generalize scattering phase function models, demonstrate an expanded translucent appearance space, and discover perceptually-meaningful translucency controls by analyzing thousands of images with computation and psychophysics.

vss

Effects of Shape and Color on the Perception of Translucency
Bei Xiao, Ioannis Gkioulekas, Asher Dunn, Shuang Zhao, Todd Zickler, Edward H. Adelson, Kavita Bala
Vision Science Society Annual Meeting (VSS) 2012
paper | project page

We study how translucency perception is related to color and object geometry, by measuring perceptual similarities between images rendered with varying combinations of scattering parameters, color and shape.

microvision

Towards wide-angle micro vision sensors
Sanjeev J. Koppal, Ioannis Gkioulekas, Travis Young, Hyunsung Park, Kenneth B. Crozier, Geoffrey L. Barrows, Todd Zickler
To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence
paper | project page

This is the journal version of our CVPR 2011 paper and includes more detailed analysis, new miniaturized prototypes, and a deployment on a micro-robotic air vehicle.

sparseldr

Dimensionality Reduction Using the Sparse Linear Model
Ioannis Gkioulekas, Todd Zickler
Advances in Neural Information Processing Systems (NIPS) 2011
paper | project page

We use the sparse linear model to learn low-dimensional linear projections that approximately preserve inner products between sparse codes, used to represent various classes of signals.

microsensor

Wide-angle Micro Sensors for Vision on a Tight Budget
Sanjeev J. Koppal, Ioannis Gkioulekas, Todd Zickler, Geoffrey L. Barrows
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2011
paper | project page

We propose and analyze a class of vision sensors that can be used on micro-scale devices with severe power and mass constraints, for tasks such as locating edges, tracking targets, and detecting faces.

surprise

Spatial Bayesian Surprise for Image Saliency and Quality Assessment,
Ioannis Gkioulekas, Giorgos Evangelopoulos, Petros Maragos
IEEE International Conference on Image Processing (ICIP) 2010
paper | project page

We propose and analyze a class of vision sensors that can be used on micro-scale devices with severe power and mass constraints, for tasks such as locating edges, tracking targets, and detecting faces.

Teaching

CS283 Computer Vision - Fall 2013 (Harvard)

CS283 Computer Vision - Fall 2012 (Harvard)

CS283 Computer Vision - Fall 2010 (Harvard)

Code

All of my released code is hosted on my GitHub account. I use the coding and style conventions described here in all of my projects.

libslm A machine learning library with emphasis on regularized (sparsity, nuclear norm, group norms) optimization and kernelization, for problems such as regression, coding, dimensionality reduction, and metric learning. Written in C/C++, with MATLAB wrappers provided.
blas_ext A linear algebra library of extensions to BLAS and LAPACK for dense matrices. Includes Cholesky and QR updates, downdates and row/column modifications, SVD and EIG updates, ports of PROPACK and ARPACK, Nystrom methods, and other randomized decompositions. Written in C, with MATLAB wrappers provided.
image_utils A library of image processing utilities. Includes implementations of many algorights for high dynamic range imaging (LDR-to-HDR, HDR image formats read/write, tonemapping), color transformations and editing, hyperspectral image editing. Written in C/C++ and MATLAB.
mex_utils A set of C++ header files for interfacing with the MATLAB mex API.
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