Automated detection of viewer engagement by head motion analysis

Güler, Uğur
Measuring viewer engagement plays a crucial role in education and entertainment. In this study we analyze head motions of the viewers from video streams to automatically determine their engagement level. Due to unavailability of a dataset for such an application, we have built our own dataset. By using face detection system, the head position of viewer is obtained throughout the video for each frame. Then, using these positions, we analyze and extract some features. In order to classify the data, we employ both Random Forest and Support Vector Machine (SVM) with extracted parameters. User engagement detection is performed using the employed model and the results indicate accuracy of 89.4% and recall of 90.9% on our dataset with Random Forest.


Optical flow based video frame segmentation and segment classification
Akpınar, Samet; Alpaslan, Ferda Nur; Department of Computer Engineering (2018)
Video information retrieval is a field of multimedia research enabling us to extract desired semantic information from video data. In content-based video information retrieval, visual content obtained from video scenes is utilized. For developing methods to cope with content-based video information retrieval in terms of temporal concepts such as action, event, etc., representation of temporal information becomes critical. In this thesis, action detection is tackled based on a temporal video representation m...
Camera electronics and image enhancement software for infrared detector arrays
Küçükkömürler, Alper; Akın, Tayfun; Department of Environmental Engineering (2012)
This thesis aims to design and develop camera electronics and image enhancement software for infrared detector arrays. It first discusses the camera electronics suitable for infrared detector arrays, then it concentrates on image enhancement software that are implemented including defective pixel correction, contrast enhancement, noise reduction and pseudo coloring. After that, testing and results of the implemented algorithms were presented. Camera electronics and circuit operation frequency are selected c...
Alignment of uncalibrated images for multi-view classification
Arık, Sercan Ömer; Vural, Elif; Frossard, Pascal (2011-12-29)
Efficient solutions for the classification of multi-view images can be built on graph-based algorithms when little information is known about the scene or cameras. Such methods typically require a pairwise similarity measure between images, where a common choice is the Euclidean distance. However, the accuracy of the Euclidean distance as a similarity measure is restricted to cases where images are captured from nearby viewpoints. In settings with large transformations and viewpoint changes, alignment of im...
Digital output ROIC with single slope ADC for cooled infrared applications
Akyurek, Fatih; Bayram, Barış (2017-04-01)
The objective of this research is to develop an ADC stage integrated into ROIC which enables ROIC to have digital output. Digital output method isolates noise caused by outside mediums. At the system level, removal of the ADC proximity card reduces system complexity and volume of the IDDCA system which is important for avionic and missile applications. It also reduces the system cost associated with external ADC components. A digital output ROIC utilizing single slope ADC is fabricated using 0.18 A mu m CMO...
Guder, Mennan; Salor, Ozgul; Cadirci, Isik (2010-10-28)
In this paper, an integrated knowledge discovery strategy for high dimensional spatial power quality event data is proposed. Real time, distributed measuring of the electricity transmission system parameters provides huge number of time series power quality events. The proposed method aims to construct characteristic event distribution and interaction models for individual power quality sensors and the whole electricity transmission system by considering feasibility, time and accuracy concerns. In order to ...
Citation Formats
U. Güler, “Automated detection of viewer engagement by head motion analysis,” M.S. - Master of Science, Middle East Technical University, 2015.