RUS  ENG
Full version
JOURNALS // Program Systems: Theory and Applications // Archive

Program Systems: Theory and Applications, 2024 Volume 15, Issue 4, Pages 111–151 (Mi ps459)

Artificial intelligence and machine learning

An analytical review of architectures, models, methods and algorithms for localization and tracking of non-rigid objects

G. G. Gritsenko, V. P. Fralenko

Ailamazyan Program Systems Institute of Russian Academy of Sciences

Abstract: Computer vision requires video stream analysis, including extracting information from frames, detecting specific objects, and collecting data about them. After detection, tracking or following objects in the video stream is often required. Non-rigidity or shape variability hinders object analysis, complicates their detection and tracking, and worsens localization.
The review considers architectures, models, methods, and algorithms used in practice for detection and tracking of non-rigid objects, and highlights promising solutions.

Key words and phrases: non-rigid object, artificial neural network, deep learning, object localization, object tracking, fire and smoke detection, medical image analysis.

UDC: 004.93
BBK: 32.813.53

MSC: Primary 68T45; Secondary 68T07

Received: 08.10.2024
Accepted: 22.12.2024

DOI: 10.25209/2079-3316-2024-15-4-111-151



© Steklov Math. Inst. of RAS, 2025