Anotation
Human body segmentation into particular body parts (regions) is a crucial task in many human body-oriented computer vision applications. In general, body segmentation as a preprocessing step can be helpful in understanding the skeletal and body structure of a human subject. Applying the segmentation methods on 3D human data is an important task, since 3D data has potential to provide additional information over RGB images, and tends to yield more accurate results.
Goal
The aim of the bachelor thesis is to examine the human body segmentation task and apply various methods on human body datasets for the purpose of body part segmentation into individual regions with the highest possible accuracy. Evaluate and compare these methods and sumarize the results. Part of the work is to to study the principles of neural networks and appropriate deep learning framework. The thesis focuses on researching exclusively synthetic data.
Timeline
Diary
03.11.2021 Website has been created
10.12.2021 I have studied some papers
31.01.2022 I had completed initial 10 pages of Related Work
14.02.2022 This weekend i started with ML on MacOs and passed some tutorials
21.02.2022 I work with UBC3V dataset - depth maps
28.02.2022 Depth maps are normalized and prepared as numpy array with ground truth
06.03.2022 !! I had some issues with training Adapted Alexnet model
07.03.2022 Website has been updated
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email: toma6@uniba.sk