Compensation for latency in XR offloaded tasks using pose prediction
(2024) MAMM15 20241Department of Design Sciences
- Abstract
- As Augmented Reality (AR) and Mixed Reality (MR) glasses continue to advance, becoming more compact and user-friendly, certain computationally demanding tasks are being offloaded to edge networks or the cloud. This shift, while enhancing the capabilities of AR/MR glasses, will introduce a new challenge—latency.
Latency occurs when there is a need to transmit data to a remote processing unit, perform tasks, and then send the processed information back to the device for rendering. Poor network conditions prevent the timely rendering of content on AR/MR glasses which negatively impacts the user experience and in worst case could lead to
Virtual Reality (VR) sickness.
In this thesis, we will focus on minimizing the perceived latency to... (More) - As Augmented Reality (AR) and Mixed Reality (MR) glasses continue to advance, becoming more compact and user-friendly, certain computationally demanding tasks are being offloaded to edge networks or the cloud. This shift, while enhancing the capabilities of AR/MR glasses, will introduce a new challenge—latency.
Latency occurs when there is a need to transmit data to a remote processing unit, perform tasks, and then send the processed information back to the device for rendering. Poor network conditions prevent the timely rendering of content on AR/MR glasses which negatively impacts the user experience and in worst case could lead to
Virtual Reality (VR) sickness.
In this thesis, we will focus on minimizing the perceived latency to enhance the user experience in AR/MR applications. Our primary approach involves using head movement tracking with available sensors to minimize latency and synchronize content with user movements, leading to a seamless and enjoyable immersive experience. (Less) - Popular Abstract
- Imagine wearing smart glasses and spotting a cute cat. Your glasses recognize the cat and draw a box around it, but there’s a catch:
your glasses don’t handle the heavy computation themselves, instead, they send images to another computer far away, called a remote server, that performs these tasks.
However, there’s a problem: by the time your glasses get the data back from the server, you
might have moved your head, and now the box is no longer around the cat.
This delay, known as latency, often disrupts the seamless integration of virtual content with the
real world. This thesis focuses on minimizing perceived latency.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9157476
- author
- Yazdanian, Yas LU and Péter, Bálint LU
- supervisor
- organization
- course
- MAMM15 20241
- year
- 2024
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- compensation, latency, XR, offloading, pose prediction
- language
- English
- id
- 9157476
- date added to LUP
- 2024-06-05 10:29:44
- date last changed
- 2024-06-05 10:29:44
@misc{9157476, abstract = {{As Augmented Reality (AR) and Mixed Reality (MR) glasses continue to advance, becoming more compact and user-friendly, certain computationally demanding tasks are being offloaded to edge networks or the cloud. This shift, while enhancing the capabilities of AR/MR glasses, will introduce a new challenge—latency. Latency occurs when there is a need to transmit data to a remote processing unit, perform tasks, and then send the processed information back to the device for rendering. Poor network conditions prevent the timely rendering of content on AR/MR glasses which negatively impacts the user experience and in worst case could lead to Virtual Reality (VR) sickness. In this thesis, we will focus on minimizing the perceived latency to enhance the user experience in AR/MR applications. Our primary approach involves using head movement tracking with available sensors to minimize latency and synchronize content with user movements, leading to a seamless and enjoyable immersive experience.}}, author = {{Yazdanian, Yas and Péter, Bálint}}, language = {{eng}}, note = {{Student Paper}}, title = {{Compensation for latency in XR offloaded tasks using pose prediction}}, year = {{2024}}, }