Dec 11, 2019   4:55 a.m. Hilda
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Ing. Marek Jakab
Identification number: 5669
University e-mail: marek.jakab [at] stuba.sk
 
Výskumný pracovník s VŠ vzdelaním - Institute of Computer Engineering and Applied Informatics (FIIT)
 
2511V00  Applied Informatics D-AI
FIIT D-AI den [year 3]
Doctoral type of study, full-time, attendance method form
3rd year of study

Contacts     Graduate     Lesson     Final thesis     
Projects     Publications     Supervised theses     

Basic information

Basic information about a final thesis

Type of thesis: Diploma thesis
Thesis title:Detection and objects recognition using 3D sensors
Written by (author): Ing. Miloš Pallo
Department: Institute of Computer Engineering and Applied Informatics (FIIT)
Thesis supervisor: Ing. Marek Jakab
Opponent:doc. Ing. Vanda Benešová, PhD.
Final thesis progress:Final thesis was successfully defended.


Additional information

Additional information about the final thesis follows. Click on the language link to display the information in the desired language.

Language of final thesis:English

Slovak        English

Title of the thesis:Detection and objects recognition using 3D sensors
Summary:One of the main tasks of the computer vision is detection and object recognition. Object recognition has a big capability and usage in various application areas as a car industry, an augment reality, a security systems or a robotics. A better availability of the 3D sensors leads to a growth in research interest in the area of the actual object recognition models improvement. A model expansion with depth information leads to progress in detection accuracy and computational efficiency. The analysis of detection and object recognition models leads to focus on actual methods of machine learning as deep learning. The main focus on usage the 3D scene information acquired from Kinect v2 sensor developed by Microsoft. We design and implement method for detection and object recognition in 3D with using depth information acquired from 3D sensor in combination with the computed normals from depth data acquired from 3D sensor. This method is be based on machine learning with usage a deep learning in neural networks.
Key words:object segmentation, object recognition, neural networks

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Parts of thesis with postponed release:

Final thesis (final thesis appendices) unlimited
Reviews for final thesis unlimited