Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Articulated motion analysis via axis-based representation
Date
2007-01-01
Author
Erdem, Sezen
Tarı, Zehra Sibel
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
144
views
0
downloads
Cite This
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 perpendicular to the viewing plane. These effects are later revealed in the trajectory analysis. We demonstrate preliminary experiments.
Subject Keywords
Human motion
,
Action recognition
,
Axis based representation
,
Human motion analysis
URI
https://hdl.handle.net/11511/57372
DOI
https://doi.org/10.1117/12.735005
Collections
Department of Computer Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Human motion analysis via axis based representations
Erdem, Sezen; Tarı, Zehra Sibel; Department of Computer Engineering (2007)
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 d...
Human action recognition for various input characteristics using 3 dimensional residual networks
Tüfekci, Gülin; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2019)
Action recognition using deep neural networks is a far-reaching research area which has been commonly utilized in applications such as statistical analysis of human behavior, detecting abnormalities using surveillance cameras and robotic systems. Previous studies have been performing researches to propose new machine learning algorithms and deep network architectures to obtain higher recognition accuracy levels. Instead of suggesting a network resulting in small accuracy gain, this thesis focuses on evaluat...
Object Recognition via Local Patch Labelling
Ulusoy, İlkay (2005-03-01)
In recent years the problem of object recognition has received considerable attention from both the machine learning and computer vision communities. The key challenge of this problem is to be able to recognize any member of a category of objects in spite of wide variations in visual appearance due to variations in the form and colour of the object, occlusions, geometrical transformations (such as scaling and rotation), changes in illumination, and potentially non-rigid deformations of the object itself. In...
Moving hot object detection in airborne thermal videos
Kaba, Utku; Akar, Gözde; Department of Electrical and Electronics Engineering (2012)
In this thesis, we present an algorithm for vision based detection of moving objects observed by IR sensors on a moving platform. In addition we analyze the performance of different approaches in each step of the algorithm. The proposed algorithm is composed of preprocessing, feature detection, feature matching, homography estimation and difference image analysis steps. First, a global motion estimation based on planar homography model is performed in order to compensate the motion of the sensor and moving ...
A Low cost learning based sign language recognition system
Akış, Abdullah Hakan; Akar, Gözde; Department of Electrical and Electronics Engineering (2018)
Sign Language Recognition (SLR) is an active area of research due to its important role in Human Computer Interaction (HCI). The aim of this work is to automatically recognize hand gestures consisting of the movement of hand, arm and fingers. To achieve this, we studied two different approaches, namely feature based recognition and Convolutional Neural Networks (CNN) based recognition. The first approach is based on segmentation, feature extraction and classification whereas the second one is based on segme...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
S. Erdem and Z. S. Tarı, “Articulated motion analysis via axis-based representation,” 2007, vol. 6764, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/57372.