Publications | Computer Vision Research Group (CVRG)

Combining shape-based and gradient-based classifiers for vehicle classification

Posted on 01 Jan 2015 by CVRG

Detection and Classification of Vehicles from Omnidirectional Videos using Temporal Average of Silhouettes

Posted on 01 Jan 2015 by CVRG

Introduction to Machine Learning

Posted on 01 Jan 2014 by CVRG

Reduced egomotion estimation drift using omnidirectional views

Posted on 01 Jan 2014 by CVRG

Multi-view Structure-from-Motion for Hybrid Camera Scenarios

Posted on 01 Jan 2012 by CVRG

Semih Orhan

Research interests:

Machine Learning
Computer Vision

Ph.D. : Computer Engineering, Izmir Institute of Technology (ongoing)

Yagiz Nalcakan

Yağız Nalçakan received his B.Sc. degree from Trakya University and he received M.Sc. degree from Istanbul University – Cerrahpasa. Currently, he is a Ph.D. student at Izmir Institute of Technology.

Research Interests:

Computer Vision
Deep Learning

B.Sc. : Computer Engineering, Trakya University (2015)

M.Sc. : Computer Engineering, Istanbul University (2019)

Ph.D. : Computer Engineering, Izmir Institute of Technology (ongoing)

Yalin Bastanlar

I studied civil engineering at the Middle East Technical University (METU) and obtained B.S. degree in 2001. I joined METU Informatics Institute for my graduate studies where I started to work on computer vision. I obtained M.S. and Ph.D. degrees from the Information Systems Department of Informatics Institute in April 2005 and July 2009, respectively. During my Ph.D. studies, I mostly worked on 3D computer vision especially when omnidirectional cameras are included. I was with the Perception Group at INRIA Rhone-Alpes as a visiting researcher for six months in 2008. I conducted a post-doctoral research visit to Oxford Brookes Vision Group in 2010. In 2011, I started as an Assistant Professor at the Department of Computer Engineering, Izmir Institute of Technology. In 2017, I became an Associate Professor at the same department.

Research Interests:
· 3D reconstruction from images
· Calibration and epipolar geometry of omnidirectional cameras
· Object detection/classification using cameras
· Vision for robots, visual odometry
· Machine learning for machine vision