Özbalkan, Uğur

Profile URL
https://hdl.handle.net/20.500.14627/499
Name Variants
Job Title
Araştırma Görevlisi
Email Address
ugur.ozbalkan@fbu.edu.tr
Main Affiliation
Bilgisayar Mühendisliği Bölümü
Status
Website
ORCID ID
0000-0003-0440-5390
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
MoGq4MIAAAAJ
WoS Researcher ID
Files
photo_301826.png.png (16.9 MB)

Research Topics

Domains
Physical SciencesHealth Sciences
Fields
Computer ScienceMedicine
Subfields
Artificial IntelligenceOrthopedics and Sports MedicineComputer Vision and Pattern RecognitionPhysiology
Specific Research Areas
Authorship Attribution and Profiling
Topic Modeling
Sports Performance and Training
Video Surveillance and Tracking Methods
Physical Activity and Health

Sustainable Development Goals

SDG data is not available

Publication Collaboration

Affiliation Name Count
Fenerbahçe University 3
Istanbul University-Cerrahpaşa 2
1 / 1
Data obtained from OpenAlex
Scholarly Output

1

Articles

1

WoS Citation Count

0

Scopus Citation Count

0

Filters

20251

Settings

Author of Publication: search.filters.isAuthorOfPublication.908d1ab4-2ccb-41e2-9af9-42f78033eef8

Scholarly Output Search Results

Now showing 1 - 1 of 1
  • Article
    Advancements in Human Pose Estimation: A Review of Key Studies and Findings Till 2025
    (2025) Turna, Özgür Can; Özbalkan, Uğur
    This paper presents an in-depth literature review that comprehensively covers the major developments, methods, architectures and datasets used in the field of human pose prediction up to 2025. The review covers a broad spectrum, starting with traditional methods, deep learning-based techniques, convolutional neural networks, graph-based approaches and more recently prominent transformer-based models. In addition to two-dimensional (2D) and three-dimensional (3D) human pose estimation methods, the paper analyses in detail the diversity of data sets, applications of Microsoft Kinect technology, real-time pose estimation systems and related architectural designs. Overall, the review of more than 120 papers shows that existing systems have made significant progress in terms of accuracy, computational efficiency and practical applications, but that there are still some challenges to overcome in complex scenarios such as multiple person detection, occlusion problems and outdoor environments. This in-depth analysis highlights current trends in the field, future research directions and potential applications.