Studentische Arbeiten am Lehrstuhl für Medientechnik

Tasks:

• Help students with basics of MATLAB (e.g. matrix operations, filtering, image processing, runtime errors)
• Correct some of the homework problems 
• Understand the MDSP coursework material

We offer:

• Payment according to the working hours and academic qualification
• Workload is approximately 7.5-15 hours per week from October 2019 to January 2020
• Technische Universität München especially welcomes applications from female applicants

Application:

• Please send your application with a CV and transcript per e-mail to basak.guelecyuez@tum.de 

• Matlab experience
• Background in signal or image processing is helpful

Using a teleoperation system with haptic feedback, the users can thus truly immerse themselves into a distant environment, i.e., modify it, and execute tasks without physically being present but with the feeling of being there. A typical teleoperation system with haptic feedback (referred to as a teleoperation system) comprises three main parts: the human operator OP)/master system, the teleoperator (TOP)/slave system, and the communication link/network in between [43]. During teleoperation, the slave and master devices exchange multimodal sensor information over the communication link. This work aims to develop a referenceless subjective quality index for time-delayed teleoperation system. This index is able to describe the subjective quality of experience based on a series of objective metrics.

Your work:

(1) build up a teleoperation system.

(2) design subjective test and collect enough subjective evaluation data as the ground truth.

(3) collect the objective metrics of teleoperation systems and design a training scheme based on the ground truth. Machine learning approaches may be needed.

(4) Evaluate the proposed quality index under different conditions.

C++

Your tasks:

1.      Current code refactoring and optimization

2.      New algorithm implementation

 

This work has a tight connection with the project Teleoperation over 5G networks and the IEEE standardization P1918.1.1.

https://www.ei.tum.de/lmt/forschung/ausgewaehlte-projekte/dfg-teleoperation-over-5g/

https://www.ei.tum.de/lmt/forschung/ausgewaehlte-projekte/ieee-p191811-haptic-codecs

 

C++, knowledge for control engineering and communication protocol

Microscoping roughness sensations can be captured with the vibrations induced by sliding motion over a textured surface. However, the captured signals can be affected by various factors, such as other vibrations of external systems or sensor inaccuracies. An important goal is to be able to filter signals and remove noise components and imperfections. To do this, source separation is a promising approach. The idea is to separate different components in signals originating from different sources, respectively. After separation, it is possible to remove noise components and maintain only meaningful parts of the original signal. The student shall investigate different forms of distortions in vibrotactile signals and methods to separate and remove them. 

MATLAB, basics in signal processing, basics in audio processing

Low-latency live video streaming is required in many use cases, such as sports and live broadcasting of events, teleoperation, and many more. Mobile edge computing (MEC) and the real-time protocol (RTP) save significant transmission time over the network. However, due to dynamic network conditions and the lack of data retransmission, video quality may suffer. A smart protection method is required to improve the video quality, while under the constraint of low-latency video streaming.

Your responsibilities:

1. Investigate the error characteristics in various live streaming scenarios over mobile and DSL networks
2. Analyze the impact of loss and jitter on the video quality and Quality of Experience (QoE)
3. Find a solution of low-latency unequal protection of video packets
4. Implement and evaluate the solution

Requirements:

• Knowledge of video codec (H264), video streaming technology (RTP, forward error correction)
• Basic knowledge of mobile networks, video quality assessment, QoE
• Mastering more than one programming language, C++ and Python preferred

We offer:

• Professional and close supervision at the young Munich-based company Smart Mobile Labs
• Hands-on experience of live video streaming over mobile networks in real product platforms
• Opportunities of accessing the state-of-the-art SW development environment: gitlab, docker, AWS cloud
• The innovative power and flexibility of a startup company

Smart Mobile Labs GmbH - Founded in 2013, Munich-based Smart Mobile Labs GmbH has set itself the goal of revolutionizing the global market for live video. The vision is to become the worlds most successful moving-picture transmission company in real time.
We are thrilled to set new standards in real-time transmission. Our team is made up of young talents and experienced managers. We combine our knowledge in live experience creation with the motivation to always give our customers a head start in no matter what business area.

In this work the student is provided with 2D images and a 3D point cloud from our drone simulation. This sensor data shall be used to verify the completeness of an aircraft inspection, which was done in the simulation. The first part will be to register the images with the point cloud in order to have a single coordinate system. The next step is to perform ray casting from every pixel into the point cloud and mark the points which get hit by the rays. This shall be done with all images which were taken during the aircraft inspection by the drone simulation. The final goal is to compute a metric how much of the aircrafts surface was inspected by the drone. The work has a strong focus on ROS and C++, so students with experience will be preferred.

C++, ROS