Expression Analysis in Paintings
For the exhibition entitled “Emotions: Pain and pleasure in Dutch painting of the Golden Age” in Frans Hals Museum, Haarlem, The Netherlands, we have developed an automatic system to analyze facial expressions in paintings of faces. Using the resulting system, face paintings in the exhibition were interpreted in terms of basic emotions such as happiness, sadness, fear, anger, surprise, disgust, and contempt. Estimated facial expressions have been visually represented to visitors of Frans Hals Museum. The results of the automatic analysis reveal the high quality of emotion portrayals produced in the sixteenth and seventeenth centuries. This work is supported by Insidde project under the European Union Seventh Framework Programme.
Expression Dynamics for Age Estimation
Estimation of a person's age from the facial image has many applications,ranging from biometrics and access control to cosmetics and entertainment. Many image-based methods have been proposed for this problem. In this research, we propose a method for the use of facial expression dynamics in age estimation.
Detection of Smile Spontaneity
Smiling is an indispensable element of nonverbal social interaction. Besides, automatic distinction between spontaneous and posed expressions is important for visual analysis of social signals. Therefore, we propose a method to distinguish between spontaneous and posed enjoyment smiles by using the dynamics of eyelid, cheek, and lip corner movements.
UvA-NEMO Smile Database
To analyze the dynamics of spontaneous/posed enjoyment smiles, we collected the UvA-NEMO Smile Database. UvA-NEMO Smile Database is a large-scale smile database which has 1240 smile videos (597 spontaneous and 643 posed) from 400 subjects. Ages of subjects vary from 8 to 76 years. Videos are in RGB color and recorded with a resolution of 1920×1080 pixels at a rate of 50 frames per second under controlled illumination conditions. For further illumination and color normalization, a color chart is present on the background of the videos.
Facial Feature Point Localization
The details and experimental protocols of our 2D facial feature point localization method can be accessed from the link below. This method was developed in cooperation with Dr. Albert Ali Salah and Prof. Theo Gevers.
Part-Based 3D Face Recognition
My M.Sc. Thesis's title is "Part-Based 3D Face Recognition Under Pose and Occlusion Variations". This thesis was supervised by Prof. Lale Akarun and co-advised by Dr. Berk Gökberk.
Free-Hand Graph Recognizer
My B.Sc. Engineering Project was on Intelligent Human-Computer Interfaces. I have developed a Free-Hand Sketch Recognizer for Graphs in cooperation with Dr. T. Metin Sezgin from Design Rationale Group in CSAIL @ Massachusetts Institute of Technology. Project was supervised by Assist. Prof. Ender Ozcan.
Virtual Tour
Here you can find a Virtual Reality Application in which you can have a tour in Yeditepe University Computer Engineering Department. This project was developed by Hamdi Dibeklioglu, Can Aydogdu, Okay Aslan and supervised by Assist. Prof. Peter Panfilov (Spring 2005). This project was also presented at Yeditepe University Computer Engineering Stand in CeBIT Bilişim Eurasia 2005 (ISTANBUL).
