@conference{designing_for_automated24,

title = {Designing for Automated Sports Commentary Systems},

author = {Peter Andrews and Oda Elise Nordberg and Frode Guribye and Morten Fjeld and Njål Borch },

url = {https://mediafutures.no/designing_for_automated_sports_commentary_systems-2/},

year  = {2024},

date = {2024-06-12},

booktitle = {IMX'24},

abstract = {Advancements in Natural Language Processing (NLP) and Computer Vision (CV) are revolutionizing how we experience sports broadcasting. Traditionally, sports commentary has played a crucial role in enhancing viewer understanding and engagement with live games. Yet, the prospects of automated commentary, especially in light of these technological advancements and their impact on viewers’ experience, remain largely unexplored. This paper elaborates upon an innovative automated commentary system that integrates NLP and CV to provide a multimodal experience, combining auditory feedback through text-to-speech and visual cues, known as italicizing, for real-time in-game commentary. The system supports color commentary, which aims to inform the viewer of information surrounding the game by pulling additional content from a database. Moreover, it also supports play-by-play commentary covering in-game developments derived from an event system based on CV. As the system reinvents the role of commentary in sports video, we must consider the design and implications of multimodal artificial commentators. A focused user study with eight participants aimed at understanding the design implications of such multimodal artificial commentators reveals critical insights. Key findings emphasize the importance of language precision, content relevance, and delivery style in automated commentary, underscoring the necessity for personalization to meet diverse viewer preferences. Our results validate the potential value and effectiveness of multimodal feedback and derive design considerations, particularly in personalizing content to revolutionize the role of commentary in sports broadcasts.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Footyvision1,

title = {FootyVision: Multi-Object Tracking, Localisation, and Augmentation of Players and Ball in Football Video},

author = {Peter Andrews and Njål Borch and Morten Fjeld},

url = {https://mediafutures.no/peterandrews-footyvision-icmip24-final/},

year  = {2024},

date = {2024-04-20},

booktitle = {ACM ICMIP},

abstract = {Football video content analysis is a rapidly evolving field aiming to enrich the viewing experience of football matches. Current research often focuses on specific tasks like player and/or ball detection, tracking, and localisation in top-down views. Our study strives to integrate these efforts into a comprehensive Multi-Object Tracking (MOT) model capable of handling perspective transformations. Our framework, FootyVision, employs a YOLOv7 backbone trained on an extended player and ball dataset. The MOT module builds a gallery and assigns identities via the Hungarian algorithm based on feature embeddings, bounding box intersection over union, distance, and velocity. A novel component of our model is the perspective transformation module that leverages activation maps from the YOLOv7 backbone to compute homographies using lines, intersection points, and ellipses. This method effectively adapts to dynamic and uncalibrated video data, even in viewpoints with limited visual information. In terms of performance, FootyVision sets new benchmarks. The model achieves a mean average precision (mAP) of 95.7% and an F1-score of 95.5% in object detection. For MOT, it demonstrates robust capabilities, with an IDF1 score of approximately 93% on both ISSIA and SoccerNet datasets. For SoccerNet, it reaches a MOTA of 94.04% and shows competitive results for ISSIA. Additionally, FootyVision scores a HOTA(0) of 93.1% and an overall HOTA of 72.16% for the SoccerNet dataset. Our ablation study confirms the effectiveness of the selected tracking features and identifies key attributes for further improvement. While the model excels in maintaining track accuracy throughout the testing dataset, we recognise the potential to enhance spatial-location accuracy.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{AIComment,

title = {AiCommentator: A Multimodal Conversational Agent for Embedded Visualization in Football Viewing},

author = {Peter Andrews and Oda Elise Nordberg and Frode Guribye and Kazuyuki Fujita and Morten Fjeld and Njål Borch},

url = {https://mediafutures.no/acm_iui_24_aicommentator_peterandrews-1/},

year  = {2024},

date = {2024-03-18},

urldate = {2024-03-18},

journal = {Intelligent User Interfaces (IUI)},

abstract = {Traditionally, sports commentators provide viewers with diverse information, encompassing in-game developments and player performances. Yet young adult football viewers increasingly use mobile devices for deeper insights during football matches. Such insights into players on the pitch and performance statistics support viewers’ understanding of game stakes, creating a more engaging viewing experience. Inspired by commentators’ traditional roles and to incorporate information into a single platform, we developed AiCommentator, a Multimodal Conversational Agent (MCA) for embedded visualization and conversational interactions in football broadcast video. AiCommentator integrates embedded visualization, either with an automated non-interactive or with a responsive interactive commentary mode. Our system builds upon multimodal techniques, integrating computer vision and large language models, to demonstrate ways for designing tailored, interactive sports-viewing content. AiCommentator’s event system infers game states based on a multi-object tracking algorithm and computer vision backend, facilitating automated responsive commentary. We address three key topics: evaluating young adults’ satisfaction and immersion across the two viewing modes, enhancing viewer understanding of in-game events and players on the pitch, and devising methods to present this information in a usable manner. In a mixed-method evaluation (n=16) of AiCommentator, we found that the participants appreciated aspects of both system modes but preferred the interactive mode, expressing a higher degree of engagement and satisfaction. Our paper reports on our development of AiCommentator and presents the results from our user study, demonstrating the promise of interactive MCA for a more engaging sports viewing experience. Systems like AiCommentator could be pivotal in transforming the interactivity and accessibility of sports content, revolutionizing how sports viewers engage with video content.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Ly2022,

title = {360TourGuiding: Towards Virtual Reality Training for Tour Guiding},

author = {Duy-Nam Ly and Thanh-Thai La and Khanh-Duy Le and Cuong Nguyen and Morten Fjeld and Thanh Ngoc-Dat Tran and Minh-Triet Tran

},

url = {https://mediafutures.no/3528575-3551436-compressed-4/},

year  = {2022},

date = {2022-09-27},

urldate = {2022-09-27},

booktitle = {360TourGuiding: Towards Virtual Reality Training for Tour Guiding},

abstract = {Tour guiding plays an important role in turning sightseeing tours into memorable experiences. Tour guides, especially inexperienced ones, must practice intensively to perfect their craft. It is key that guides acquire knowledge about sights, in-situ presentation skills, and perfection ability to interact with and engage tourists. Therefore, tour-guide education requires on-site training at the place of interest including live tourist audiences. However, for modest budgets, such setups are costly and tourism students have to practice tour guiding at home or in simulated class-room setups. It has become a challenge for students to adequately prepare themselves for jobs in terms of relevant knowledge and skills. To tackle this problem, we propose 360TourGuiding, a VR system enabling its users to practice tour guiding with 360 travel videos plus the attendance of remote audiences participating through their mobile and personal device. This paper reports on the concept, on our design, current implementation, and on a pilot study with the current 360TourGuiding prototype. Based on qualitative feedback gained through the pilot study, we discuss possible system improvements, future system updates, and plans for empirical evaluation.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Wang2022,

title = {A Collaborative System of Flying and Ground Robots with Universal Physical Coupling Interface (PCI), and the Potential Interactive Applications},

author = {Ziming Wang and Ziyi Hu and Yemao Man and Morten Fjeld},

year  = {2022},

date = {2022-04-29},

urldate = {2022-04-29},

booktitle = {A Collaborative System of Flying and Ground Robots with Universal Physical Coupling Interface (PCI), and the Potential Interactive Applications},

abstract = {Flying and ground robots complement each other in terms of their advantages and disadvantages. We propose a collaborative system combining flying and ground robots, using a universal physical coupling interface (PCI) that allows for momentary connections and disconnections between multiple robots/devices. The proposed system may better utilize the complementary advantages of both flying and ground robots. We also describe various potential scenarios where such a system could be of benefit to interact with humans - namely, remote field works and rescue missions, transportation, healthcare, and education. Finally, we discuss the opportunities and challenges of such systems and consider deeper questions which should be studied in future work.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Fjeld2022,

title = {RedirectedDoors: Redirection While Opening Doors in Virtual Reality},

author = {Morten Fjeld and Yukai Hoshikawa and Kazuyuki Fujita and Kazuki Takashima and Yoshifumi Kitamura },

year  = {2022},

date = {2022-03-12},

urldate = {2022-03-12},

booktitle = {RedirectedDoors: Redirection While Opening Doors in Virtual Reality.},

abstract = {We propose RedirectedDoors, a novel technique for redirection in VR focused on door-opening behavior. This technique manipulates the user's walking direction by rotating the entire virtual environment at a certain angular ratio of the door being opened, while the virtual door's position is kept unmanipulated to ensure door-opening realism. Results of a user study using two types of door-opening interfaces (with and without a passive haptic prop) revealed that the estimated detection thresholds generally showed a higher space efficiency of redirection. Following the results, we derived usage guidelines for our technique that provide lower noticeability and higher acceptability.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Le2021b,

title = {VXSlate: Combining Head Movement and Mobile Touch for Large Virtual Display Interaction},

author = {Khanh-Duy Le and Tanh Quang Tran and Karol Chlasta and Krzysztof Krejtz and Morten Fjeld and Andreas Kunz},

url = {https://conferences.computer.org/vrpub/pdfs/VRW2021-2ANNoldm4A10Ml9f63uYC9/136700a528/136700a528.pdf

https://www.youtube.com/watch?v=N8ZJlKWj4mk&ab_channel=DuyL%C3%AAKh%C3%A1nh},

doi = { 10.1109/VRW52623.2021.00146},

year  = {2021},

date = {2021-02-12},

pages = {528-529},

publisher = {IEEE The Institute of Electrical and Electronics Engineers, Inc.},

organization = {2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW).},

abstract = {Virtual Reality (VR) headsets can open opportunities for users to accomplish complex tasks on large virtual displays, using compact setups. However, interacting with large virtual displays using existing interaction techniques might cause fatigue, especially for precise manipulations, due to the lack of physical surfaces. We designed VXSlate, an interaction technique that uses a large virtual display, as an expansion of a tablet. VXSlate combines a user’s head movements, as tracked by the VR headset, and touch interaction on the tablet. The user’s head movements position both a virtual representation of the tablet and of the user’s hand on the large virtual display. The user’s multi-touch interactions perform finely-tuned content manipulations.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}