View Proposal

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Proposer

Radu-Casian Mihailescu

Title

Neural Depth Estimation - Collaboration with TII

Goal

Description

This master’s thesis proposal explores the use of a combination of analytical and deep learning-based solutions to obtain accurate monocular metric depth estimation from a sequence of frames. The research aims to address the need of a reliant and robust depth estimator for on-board integration on computationally constrained platforms for online metric depth estimation. The project includes collecting datasets from relevant sources, perform the necessary literature review, and using established computer vision and machine learning techniques to implement a working demo. The expected architecture will be a hybrid analytical-deep learning depth estimation pipeline, combining traditional well-established techniques with state-of-the-art deep learning approaches to improve the performance and accuracy of metric depth estimation. More specifically, the first stage will be tasked of computing a sparse depth matrix –D*- using the inverse pinhole camera model with established sparse optical flow techniques (e.g. Kanade-Shi-Tomasi, or Deep Patch optical flow). The second stage will be a neural network (e.g. ViT, TCN) that considers as input a sequence of RGB-D* frames and outputs the current metric depth map. The final architecture will be tested in a fixed-wing drone scenario flying at ~200 meters of altitude.

Resources

Background

 Machine Learning and Deep Learning: Understanding machine learning algorithms, especially those used in Computer Vision, and deep learning frameworks like PyTorch is crucial.  Computer Vision: basic knowledge of CV algorithms, especially related to sparse optical flow and inverse projection transformation  Python Programming: Python is the primary language for most machine learning and NLP tasks, so a strong command of Python is essential.

Url

Difficulty Level

Variable

Ethical Approval

None

Number Of Students

1

Supervisor

Radu-Casian Mihailescu

Keywords

Degrees

Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Bachelor of Science in Information Systems
Bachelor of Science in Software Development for Business (GA)
Master of Engineering in Software Engineering
Master of Design in Games Design and Development
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Business Information Management
Master of Science in Computer Science for Cyber Security
Master of Science in Computer Systems Management
Master of Science in Computing (2 Years)
Master of Science in Data Science
Master of Science in Human Robot Interaction
Master of Science in Information Technology (Business)
Master of Science in Information Technology (Software Systems)
Master of Science in Network Security
Master of Science in Robotics
Master of Science in Software Engineering
Bachelor of Science in Computing Science
Bachelor of Engineering in Robotics
Bachelor of Science in Computer Science (Cyber Security)
Master of Science in Robotics with Industrial Application
Postgraduate Diploma in Artificial Intelligence