Neven Pičuljan

I created a feasibility study and demo for a face recognition system that I developed at Visage Technologies. The demo was written in C/C++ and Python. I collaborated with the Swedish Police, the Swedish National Forensic Centre, and the Swedish Defence Research Agency on this project.

A neural network for function approximation using the Levenberg-Marquardt algorithm. I tested the code on various functions and used Torch framework and Python.

A simple classifier in R for credit card applications. I was given a data set with users’ interactions and experimented with various machine learning algorithms: SVMs, decision trees, random forests, logistic regression, etc.

A project in data mining. I was given a data set with detailed information about interactions of visitors with different stations at Copernicus Science Centre in Warsaw, Poland. The goal was to characterize the flow of visitors through these stations and to segment visitors into separate categories/segments. I used R.

A system for detection and localization of a 2D contour (human head) in an image, where many such contours of different size could exist. For this purpose, I applied the generalized Hough Transform (GHT). The system was written in Python.

An implementation of various operations on graphs in LISP: finding cycles in graphs, finding paths from one node to another in graphs, checking if the binary tree is symmetric, depth-first order graph traversal, finding maximum depth of a binary tree, and finding a leaf with a maximum value in a binary tree.

An expert system created in Prolog for animal identification.

A face recognition system. It was trained and tested in Torch framework. The data set was made of publicly available data sets.

Research conducted on different algorithms for face alignment.

A system to automate the classification of Stack Overflow's posts in the answer thread into three categories: One for those that answer the question well. Another for those that can be potentially useful to the user (e.g., because they can help educate him/her on the subject). Lastly, group those that are just bad or useless.

I experimented with various machine learning algorithms (scikit-learn): Gaussian naive Bayes, SVMs, and random forests.

A system to do pedestrian detection in urban environments using contour based detection. It was written in Python using Numpy, Scikit-learn, and OpenCV.

Performance-driven animation as a web application. Face tracking was used to gain motion in the face of an animated virtual character. The graphics system used to build the application was Three.js based on WebGL. The face-tracking system used to build the application was Visage|SDK.

A computer game controlled with head movements. It was written in C# using Unity game engine.