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2018 Proceeding- General Chairs:
- Rainer Lienhart,
- Thomas B. Moeslund,
- Hideo Saito,
- Rainer Lienhart
It is our great pleasure to welcome you to the 1st ACM International Workshop on Multimedia Content Analysis in Sports (ACM MMSports'18). The workshop is co-located with ACM Multimedia 2018 in Seoul, Korea. It addresses a very timely topic because the influence of rapidly developing technologies has changed the way of how we participate, watch, understand and research sports. For example, television broadcasts augment live video footage with computer vision-based graphics in real time to emphasize different aspects of a game or performance and assist focus and understanding of viewers. Moreover, the astonishing impact of wearables within the last years plays a pivotal role in how we pursue and evaluate our personal training goals. In a professional setting, coaches and training scientists directly benefit from the latest technological research, reshaping the way we think about improving the performance and technique of athletes, understand sport injuries or enhance the qualitative and quantitative analyses of performances.
While research fields like computer vision, sensor technology, machine learning and data driven approaches recently made huge advancements and have massively influenced many aspects of sports, the joint assessment of multiple modalities for sport technologies offers appealing innovations to advance the field. For example, audio-visual cues are used for classifying different sport types or performing crowed sentiment analyses. Computer vision systems using highspeed camera arrays generate performance coefficients and perform technical game analyses, while force predictions from force plates and wearable sensors can be utilized to predict impending injuries.
This workshop wants to bring together the breadth and depth of these diverse approaches in order to stimulate each other with new ideas and foster research progress.
The call for papers for this new workshop attracted 23 high-quality submissions from around the world of which 12 were accepted (52%). We are also proud to have two distinguished invited talk presentations: One from academia (Makio Kashino, Head of Sports Brain Science Project @ NTT Communication Science Laboratories & Specially-Appointed Professor in the School of Engineering, Tokyo Institute of Technology) and one from industry (Tuukka Karvonen, Qoncept Inc).
Proceeding Downloads
Understanding and Shaping the Athlete's Brain Using Body-Mind Reading and Feedback
In sports where athletes play against an opponent, for example, ballgames and martial arts, a variety of cognitive functions hold the key to winning, such as grasping the situation, strategizing against one's opponent, making appropriate decisions ...
Snooker Video Event Detection Using Multimodal Features
The key to content-based video retrieval is the automatic detection and annotation of semantic events. In view of the problem that the results of existing research on snooker video analysis cannot satisfy event detection needs, we propose a system for ...
A Convolutional Sequence to Sequence Model for Multimodal Dynamics Prediction in Ski Jumps
A convolutional sequence to sequence model for predicting the jump forces of ski jumpers directly from pose estimates is presented. We collect the footage of multiple, unregistered cameras together with the output of force measurement plates and present ...
Stillness Moves: Exploring Body Weight-Transfer Learning in Physical Training for Tai-Chi Exercise
- Han Hong Lin,
- Ping Hsuan Han,
- Kuan Yin Lu,
- Chia Hung Sun,
- Pei Yi Lee,
- Yao Fu Jan,
- Amy Ming Sui Lee,
- Wei Zen Sun,
- Yi Ping Hung
Body weight-transfer plays an important role in many exercises. The correlation of the body posture, movement, and weight-transfer will mutually affect the trainee to do well in performances such as Tai-Chi exercise. According to the traditional way of ...
An On-site Visual Feedback Method Using Bullet-Time Video
This paper describes an on-site visual feedback method that executes all processes from capturing of multi-view videos to generating and displaying bullet-time videos in real-time. In order to realize the on-site visual feedback in a dynamic scene where ...
Using Virtual Reality and Head-Mounted Displays to Increase Performance in Rowing Workouts
Technology is advancing rapidly in the domain of virtual reality, as well as in using sensors to gather feedback from our body and the environment we are interacting in. Combining these two technologies gives us the opportunity to create personalized ...
ORSNet: A Hybrid Neural Network for Official Sports Referee Signal Recognition
In this work, we propose a novel sports referee training system based on wearable sensors and a real-time Official Referee Signal (ORS) segmentation/recognition method which can recognize 65 kinds basketball ORSs with the accuracy of 95.3%. A hybrid ...
Development of a Virtual Environment for Motion Analysis of Tennis Service Returns
In sports performance analysis, it is important to understand differences between experts and novices in order to train novices in an efficient manner. To understand these differences within the game of tennis, we developed a virtual environment to ...
Swimming Pool Occupancy Analysis using Deep Learning on Low Quality Video
Automatically creating spatio-temporal occupancy analysis of public swimming pools is of great interest, both for administrators to optimize the use of these expensive facilities, and for users to schedule their activities outside peak hours. In this ...
Practical Sports Video Analysis at Qoncept: A Few Case Studies
Analyzing sports scenarios through video processing is an enticing approach to sports analytics, especially due to the lack of need to attach sensors to the measured target. However, it has many challenges inherent to inverse problems such as ...
Sports Video Captioning by Attentive Motion Representation based Hierarchical Recurrent Neural Networks
Sports video captioning is a task of automatically generating a textual description for sports events (e.g. football, basketball or volleyball games). Although previous works have shown promising performance in producing the coarse and general ...
Estimation of Runners' Number of Steps, Stride Length and Speed Transition from Video of a 100-Meter Race
The purpose of this study is sensing movements of 100-m runners from video that is publicly available, for example, Internet broadcasts. Normally, information that can be obtained from a video is limited to the number of steps and average stride length. ...
Fast and Accurate Object Detection Using Image Cropping/Resizing in Multi-View 4K Sports Videos
Recently, fast and accurate DNN object detectors such as YOLO and SSD have attracted considerable attention. However, it still takes far more time than real time processing when inputting a 4K video and becomes even more challenging when inputting multi-...
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Acceptance Rates
| Year | Submitted | Accepted | Rate |
|---|---|---|---|
| MMSports '22 | 26 | 17 | 65% |
| MMSports'18 | 23 | 12 | 52% |
| Overall | 49 | 29 | 59% |