ACM MM’25 Demo: SDART: Spatial Dart AR Simulation with Hand-Tracked Input

SDART: Spatial Dart AR Simulation with Hand-Tracked Input

ACM Multimedia 2025

October 27 – October 31, 2025

Dublin, Ireland

[PDF]

Milad Ghanbari (AAU, Austria), Wei Zhou (Cardiff, UK), Cosmin Stejerean (Meta, US), Christian Timmerer (AAU, Austria), Hadi Amirpour (AAU, Austria)

Abstract: We present a physics-driven 3D dart-throwing interaction system for Apple Vision Pro (AVP), developed using Unity 6 engine and running in augmented reality (AR) mode on the device. The system utilizes the PolySpatial and Apple’s ARKit software development kits (SDKs) to ensure hand input and tracking in order to intuitively spawn, grab, and throw virtual darts similar to real darts. The application benefits from physics simulations alongside the innovative no-controller input system of AVP to manipulate objects realistically in an unbounded spatial volume. By implementing spatial distance measurement, scoring logic, and recording user performance, this project enables user studies on quality of experience in interactive experiences. To evaluate the perceived quality and realism of the interaction, we conducted a subjective study with 10 participants using a structured questionnaire. The study measured various aspects of the user experience, including visual and spatial realism, control fidelity, depth perception, immersiveness, and enjoyment. Results indicate high mean opinion scores (MOS) across key dimensions. Link to video: Link

Posted in ATHENA | Comments Off on ACM MM’25 Demo: SDART: Spatial Dart AR Simulation with Hand-Tracked Input

ACM MM’25 Demo: Depth-Enabled Inspection of Medical Videos

Depth-Enabled Inspection of Medical Videos

ACM Multimedia 2025

October 27 – October 31, 2025

Dublin, Ireland

[PDF]

Hadi Amirpour (AAU, Austria), Doris Putzgruber-Adamitsch (AAU, Austria), Yosuf El-Shabrawi (Kabeg, Austria), Klaus Schoeffmann (AAU, Austria)

Abstract: Cataract surgery is the most frequently performed surgical procedure worldwide, involving the replacement of a patient’s clouded eye lens with a synthetic intraocular lens to restore visual acuity. Although typically brief, the operation consists of distinct phases that demand precision and extensive training, traditionally constrained by the limitations of real-time observation under a microscope. To enhance learning and procedural accuracy, modern advancements in stereoscopic video capture and head-mounted displays (HMDs) offer a promising solution. This paper demonstrates the application of stereoscopic cataract surgery videos, visualized through Apple Vision Pro (AVP) and Meta Quest 3, to provide immersive 3D perspectives that enhance depth perception and spatial awareness. An expert evaluation study with experienced surgeons indicates that stereoscopic visualization significantly improves comprehension of spatial relationships and procedural maneuvers, suggesting its potential to revolutionize surgical education and real-time guidance in ophthalmic surgery. Demo video: Link

Posted in ATHENA | Comments Off on ACM MM’25 Demo: Depth-Enabled Inspection of Medical Videos

 A Tutorial at  ACM SIGCOMM 2025

A Tutorial at  ACM SIGCOMM 2025

Optimizing Low-Latency Video Streaming: AI-Assisted Codec-Network Coordination

[Link]

Coimbra, Portugal, September 8 – 11, 2025.


Tutorial speakers:

  • Farzad Tashtarian (Alpen-Adria-Universität – AAU)
  • Zili Meng (Hong Kong University of Science and Technology – HKUST)
  • Abdelhak Bentaleb (Concordia University)
  • Mahdi Dolati (Sharif University of Technology)

This tutorial focuses on the emerging need for ultra-low-latency video streaming and how AI-assisted coordination between codecs and network infrastructure can significantly improve performance. Traditional end-to-end streaming pipelines are often disjointed, leading to inefficiencies under tight latency constraints. We present a cross-layer approach that leverages AI for real-time encoding parameter adaptation, network-aware bitrate selection, and joint optimization across codec behavior and transport protocols. The tutorial examines the integration of AI models with programmable network architectures (e.g., SDN, P4) and modern transport technologies such as QUIC and Media over QUIC (MoQ) to minimize startup delay, stall events, and encoding overhead. Practical use cases and experimental insights illustrate how aligning codec dynamics with real-time network conditions enhances both QoE and system efficiency. Designed for both researchers and engineers, this session provides a foundation for developing next-generation intelligent video delivery systems capable of sustaining low-latency performance in dynamic environments.

Posted in ATHENA | Comments Off on  A Tutorial at  ACM SIGCOMM 2025

Real-Time AI-Driven Avatar Generation for Sign Language in HTTP Adaptive Streaming

Real-Time AI-Driven Avatar Generation for Sign Language in HTTP Adaptive Streaming

The 3rd ACM SIGCOMM Workshop on Emerging Multimedia Systems (ACM EMS 2025)

https://conferences.sigcomm.org/sigcomm/2025/workshop/ems/

8 September 2025 // Coimbra, Portugal

[PDF]

Daniele Lorenzi (AAU, Austria), Emanuele Artioli (AAU, Austria), Farzad Tashtarian (AAU, Austria), Christian Timmerer (AAU, Austria)

Abstract: As digital media consumption over the Internet surges globally, ensuring accessibility for all users becomes paramount. For people with hearing impairments, this means providing inclusion beyond classic captioning, which does not convey the full emotional and contextual depth of spoken content. This work addresses this accessibility gap by exploring the use of AI-generated avatars capable of translating speech into sign language in real-time. After defining the multifaceted challenges in this domain, we propose a novel AI-driven task partition to animate avatars for accurate and expressive sign language interpretations in live streaming.

Posted in ATHENA | Comments Off on Real-Time AI-Driven Avatar Generation for Sign Language in HTTP Adaptive Streaming

Elsevier Displays: Unlocking Implicit Motion for Evaluating Image Complexity

Unlocking Implicit Motion for Evaluating Image Complexity

Displays

[PDF]

Yixiao Lia (Beihang University, China), Xiaoyuan Yang (Beihang University, China), Yanda Meng (University of Exeter, UK), Hadi Amirpour (AAU, AT), Jiang Liu (Cardiff University, UK), Yuqing Luo (Cardiff University, UK), Hantao Liu (Cardiff University, UK), and Wei Zhou (Cardiff University, UK)

Abstract: Image complexity (IC) plays a critical role in both cognitive science and multimedia computing, influencing visual aesthetics, emotional responses, and tasks such as image classification and enhancement. However, defining and quantifying IC remains challenging due to its multifaceted nature, which encompasses both objective attributes (e.g., detail, structure) and subjective human perception. While traditional methods rely on entropy-based or multidimensional approaches, and recent advances employ machine learning and shallow neural networks, these techniques often fail to fully capture the subjective aspects of IC. Inspired by the fact that the human visual system inherently perceives implicit motion in static images, we propose a novel approach to address this gap by explicitly incorporating hidden motion into IC assessment. We introduce the motion-inspired image complexity assessment metric (MICM) as a new framework for this purpose. MICM introduces a dual-branch architecture: One branch extracts spatial features from static images, while the other generates short video sequences to analyze latent motion dynamics. To ensure meaningful motion representation, we design a hierarchical loss function that aligns video features with text prompts derived from image-to-text models, refining motion semantics at both local (i.e., frame and word) and global levels. Experiments on three public image complexity assessment (ICA) databases demonstrate that our approach, MICM, significantly outperforms state-of-the-art methods, validating its effectiveness. The code will be publicly available upon acceptance of the paper.

 

Posted in ATHENA | Comments Off on Elsevier Displays: Unlocking Implicit Motion for Evaluating Image Complexity

Up to 4 Predoc Scientist Positions (all genders welcome)

The University of Klagenfurt, with approximately 1,700 employees and over 13,000 students, is located in the Alps-Adriatic region and consistently achieves excellent placements in rankings. The motto “per aspera ad astra” underscores our firm commitment to the pursuit of excellence in all activities in research, teaching, and university management. The principles of equality, diversity, health, sustainability, and compatibility of work and family life serve as the foundation for our work at the university.

The University of Klagenfurt is in the process of establishing a Karl Popper Kolleg (graduate school) entitled “FruitScope: A DroneScope for Smart Agriculture”. The following positions are open for applicants at this school with an anticipated starting date of October 1, 2025:

Up to 4 Predoc Scientist Positions (all genders welcome)

  • Level of employment: 75 % (30 hours per week) each
  • Minimum salary: € 39,005.40 per annum (gross); classification according to collective bargaining agreement: B1
  • Limited to: 3 years
  • Application deadline: August 20, 2025
  • Reference code: 338/25

Tasks and responsibilities:

  • Independent research and scientific qualification within the Karl Popper Kolleg FruitScope with the aim to acquire the Doctoral Degree in Technical Sciences
  • Peer-reviewed publication of scientific results in journals and at conferences
  • Team work and student mentoring
  • Active participation in public relations activities

This graduate school seeks to push the current bounds of state-of-the-art in navigation, coordination, sensing, and communication of multi agent unmanned aerial vehicles (UAVs). The groups of the involved faculty publish in international top journals and conference proceedings. Successful applicants will be encouraged and supported to publish and present their work in such journals and proceedings and will have the opportunity to cooperate with our world-renowned international partners in science and industry. We currently cooperate with partners worldwide, mainly in the USA/Canada and Europe. We specifically encourage close and open collaboration with our peers both internationally and at the University and support international exchanges with the universities and research institutions affiliated to the graduate school (e.g., ETH Zurich, MIT, CMU, NASA, UofT, U-Mich, UPenn, Georgia Tech). Our young research groups provide a dynamic, familiar, and friendly attitude and thus a collaborative and inspiring work environment with very modern infrastructure (e.g., one of the largest indoor drone halls in Europe), which is continuously updated and upgraded (e.g., soon, with one of the largest outdoor drone test fields in the world).

Prerequisites for the appointment:

  • Completed Master’s or Diploma degree in electrical engineering, information and communication engineering, mechanical engineering, computer science or related fields. This requirement has an extended deadline and must be fulfilled two weeks before the starting date at the latest; hence, the last possible deadline for meeting this requirement is September 17, 2025.
  • Proven knowledge and experience in at least one of the following areas: mobile robotics, wireless communications or sensing, multimedia communication, signal processing for communications, or machine learning
  • Proven programming skills in at least one of the following languages: Matlab, C/C++, Java, Python, ROS or similar
  • Fluency in English (both written and spoken)

Additional desired qualifications:

  • Good knowledge of cooperative software development (e.g., with GIT)
  • First scientific publication (apart from Master’s or Diploma thesis) in the area of mobile robotics, wireless sensing, or multimedia communication technology
  • Relevant international or practical experience
  • Good scientific communication and presentation skills
  • German language skills or willingness to acquire German language skills within the first two years of service
  • Social skills and ability to work independently

Our offer:

The employment contract is concluded for the position as predoc scientist and stipulates a starting salary of € 2,786.10 gross per month (14 times a year; previous experience deemed relevant to the job can be recognized).

The University of Klagenfurt also offers:

  • Personal and professional advanced training courses, management and career coaching, including bespoke training for women in science
  • Numerous attractive additional benefits, see also https://jobs.aau.at/en/the-university-as-employer/
  • Diversity- and family-friendly university culture
  • The opportunity to live and work in the attractive Alps-Adriatic region with a wide range of leisure activities in the spheres of culture, nature and sports

The application:

If you are interested in this position, please apply in English providing the following documents:

  • Letter of application explaining the motivation and including a statement of interest in research (indicating an idea for the research for your own doctoral degree)
  • Curriculum vitae (please do not include a photo)
  • Copies of degree certificates (Bachelor and Master)
  • Copies of official transcripts (Bachelor and Master) containing a list of all courses and grades
  • Master’s thesis. If the thesis is not available, the candidate should provide a draft or an explanation.
  • If an applicant has not received the Master’s degree by the application deadline, the applicant should provide a declaration, written either by a supervisor or by the candidate themselves, on the feasibility of finishing the Master’s degree before September 17, 2025.

To apply, please select the position with the reference code 338/25 in the category “Scientific Staff” using the link “Apply for this position” in the job portal at https://jobs.aau.at/en/.

Candidates must provide proof that they meet the required qualifications by August 20, 2025, at the latest. However, candidates who fulfil the required qualifications but do not yet possess the required Master’s degree can apply, provided they are able to meet this requirement at least two weeks before the starting date. Therefore, the latest possible deadline for meeting this requirement is September 17, 2025.

General information about the university as an employer can be found at https://jobs.aau.at/en/the-university-as-employer/. At the University of Klagenfurt, recruitment and staff matters are accompanied not only by the authority responsible for the recruitment procedure but also by the Equal Opportunities Working Group and, if applicable, by the Representative for Disabled Persons.

For further information on this specific vacancy, please contact:

The University of Klagenfurt aims to increase the proportion of women and therefore specifically invites qualified women to apply for the position. Where the qualification is equivalent, women will be given preferential consideration.

People with disabilities or chronic diseases, who fulfil the requirements, are particularly encouraged to apply. Travel and  accommodation costs incurred during the application process will not be refunded. Under exceptional circumstances online hearings may be possible. Translations into other languages serve informational purposes only. Solely the version advertised in the University Bulletin (Mitteilungsblatt) shall be legally binding.

Posted in News | Comments Off on Up to 4 Predoc Scientist Positions (all genders welcome)

Elsevier SPIC: 360-Degree Video Super Resolution and Quality Enhancement Challenge: Methods and Results

Signal Processing: Image Communication

[PDF]

Ahmed Telili (TII, UAE), Wassim Hamidouche (TII, UAE), Brahim Farhat (TII, UAE), Hadi Amirpour (AAU, Austria), Christian Timmerer (AAU, Austria), Ibrahim Khadraoui (TII, UAE), Jiajie Lu (Politecnico di Milano, Italy), The Van Le (IVCL, South Korea), Jeonneung Baek (IVCL, South Korea), Jin Young Lee (IVCL, South Korea), Yiying Wei (AAU, Austria), Xiaopeng Sun (Meituan Inc. China), Yu Gao (Meituan Inc. China), JianCheng Huang (Meituan Inc. China) and Yujie Zhong (Meituan Inc. China)

Omnidirectional (360-degree) video is rapidly gaining popularity due to advancements in immersive technologies like virtual reality (VR) and extended reality (XR). However, real-time streaming of such videos, particularly in live mobile scenarios such as unmanned aerial vehicles (UAVs), is hindered by limited bandwidth and strict latency constraints. While traditional methods such as compression and adaptive resolution are helpful, they often compromise video quality and introduce artifacts that diminish the viewer’s experience. Additionally, the unique spherical geometry of 360-degree video, with its wide field of view, presents challenges not encountered in traditional 2D video. To address these challenges, we initiated the 360-degree Video Super Resolution and Quality Enhancement challenge. This competition encourages participants to develop efficient machine learning (ML)-powered solutions to enhance the quality of low-bitrate compressed 360-degree videos, under two tracks focusing on 2× and 4× super-resolution (SR). In this paper, we outline the challenge framework, detailing the two competition tracks and highlighting the SR solutions proposed by the top-performing models. We assess these models within a unified framework, (i) considering quality enhancement, (ii) bitrate gain, and (iii) computational efficiency. Our findings show that lightweight single-frame models can effectively balance visual quality and runtime performance under constrained conditions, setting strong baselines for future research. These insights offer practical guidance for advancing real-time 360-degree video streaming, particularly in bandwidth-limited immersive applications.

Posted in ATHENA | Comments Off on Elsevier SPIC: 360-Degree Video Super Resolution and Quality Enhancement Challenge: Methods and Results