Human motion analysis via axis based representations

Download
2007
Erdem, Sezen
Visual analysis of human motion is one of the active research areas in computer vision. The trend shifts from computing motion fields to understanding actions. In this thesis, an action coding scheme based on trajectories of the features calculated with respect to a part based coordinate system is presented. The part based coordinate system is formed using an axis based representation. The features are extracted from images segmented in the form of silhouettes. We present some preliminary experiments that demonstrate the potential of the method in action similarity analysis.

Suggestions

3D synthetic human face modelling tool based on T-spline surfaces
Aydoğan, Ali; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2007)
In this thesis work, a 3D Synthetic Human Face Modelling Software is implemented using C++ and OpenGL. Bézier surfaces, B-spline surfaces, Nonuniform Rational B-spline surfaces, Hierarchical B-Spline surfaces and T-spline surfaces are evaluated as options for the surface description method. T-spline surfaces are chosen since they are found to be superior considering the requirements of the work. In the modelling process, a modular approach is followed. Firstly, high detailed facial regions (i.e. nose, eyes,...
Vision-assisted object tracking
Özertem, Kemal Arda; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2012)
In this thesis, a video tracking method is proposed that is based on both computer vision and estimation theory. For this purpose, the overall study is partitioned into four related subproblems. The first part is moving object detection; for moving object detection, two different background modeling methods are developed. The second part is feature extraction and estimation of optical flow between video frames. As the feature extraction method, a well-known corner detector algorithm is employed and this ext...
Visual quality assessment for stereoscopic video sequences
Sarıkan, Selim Sefa; Akar, Gözde; Department of Electrical and Electronics Engineering (2011)
The aim of this study is to understand the effect of different depth levels on the overall 3D quality and develop an objective video quality metric for stereoscopic video sequences. Proposed method is designed to be used in video coding stages to improve overall 3D video quality. This study includes both objective and subjective evaluation. Test sequences with different coding schemes are used. Computer simulation results show that overall quality has a strong correlation with the quality of the background,...
Articulated motion analysis via axis-based representation
Erdem, Sezen; Tarı, Zehra Sibel (2007-01-01)
Human motion analysis is one of the active research areas in computer vision. The trend shifts from computing motion fields to determining actions. We present an action coding scheme based on a trajectory of features defined with respect to a part based coordinate system. The method does not require prior human model or special motion capture hardware. The features are extracted from images segmented in the form of silhouettes. The feature extraction step ignores 3D effects such as self occlusions or motion...
A comparison of subspace based face recognition methods
Gönder, Özkan; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2004)
Different approaches to the face recognition are studied in this thesis. These approaches are PCA (Eigenface), Kernel Eigenface and Fisher LDA. Principal component analysis extracts the most important information contained in the face to construct a computational model that best describes the face. In Eigenface approach, variation between the face images are described by using a set of characteristic face images in order to find out the eigenvectors (Eigenfaces) of the covariance matrix of the distribution,...
Citation Formats
S. Erdem, “Human motion analysis via axis based representations,” M.S. - Master of Science, Middle East Technical University, 2007.