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In many sports, it is useful to analyse video of an athlete in competition for training purposes. In swimming, stroke rate is a common metric used by coaches; requiring a laborious labelling of each individual stroke. We show that using a…
Data visualization is the process by which data of any size or dimensionality is processed to produce an understandable set of data in a lower dimensionality, allowing it to be manipulated and understood more easily by people. The goal of…
Composite visualization represents a widely embraced design that combines multiple visual representations to create an integrated view. However, the traditional approach of creating composite visualizations in immersive environments…
Embeddings are ubiquitous in machine learning, appearing in recommender systems, NLP, and many other applications. Researchers and developers often need to explore the properties of a specific embedding, and one way to analyze embeddings is…
Video representation is a key challenge in many computer vision applications such as video classification, video captioning, and video surveillance. In this paper, we propose a novel approach for video representation that captures…
Visualizing data in sports videos is gaining traction in sports analytics, given its ability to communicate insights and explicate player strategies engagingly. However, augmenting sports videos with such data visualizations is challenging,…
The field of active matter in general and microswimming in particular has experienced a rapid and ongoing expansion over the last decade. A particular interesting aspect is provided by artificial autonomous microswimmers constructed from…
Sports data analysis is becoming increasingly large-scale, diversified, and shared, but difficulty persists in rapidly accessing the most crucial information. Previous surveys have focused on the methodologies of sports video analysis from…
The aim of visualization is to support people in dealing with large and complex information structures, to make these structures more comprehensible, facilitate exploration, and enable knowledge discovery. However, users often have problems…
One huge advantage of Augmented Reality (AR) is its numerous possibilities of displaying information in the physical world, especially when applying Situated Analytics (SitA). AR devices and their respective interaction techniques allow for…
Depth perception in volumetric visualization plays a crucial role in the understanding and interpretation of volumetric data. Numerous visualization techniques, many of which rely on physically based optical effects, promise to improve…
This thesis develops and evaluates effective techniques for visualisation of flows (e.g. of people, trade, knowledge) between places on geographic maps. This geographically-embedded flow data contains information about geographic locations,…
Video Captioning is considered to be one of the most challenging problems in the field of computer vision. Video Captioning involves the combination of different deep learning models to perform object detection, action detection, and…
Ubiquitous sensors and Internet of Things (IoT) technologies have revolutionized the sports industry, providing new methodologies for planning, effective coordination of training, and match analysis post game. New methods, including machine…
Advanced wearable sensor devices have enabled the recording of vast amounts of movement data from individuals regarding their physical activities. This data offers valuable insights that enhance our understanding of how physical activities…
Business process models are usually visualized using 2D representations. However, multiple attributes contained in the models such as time, data, and resources can quickly lead to cluttered and complex representations. To address these…
Videos are an accessible form of media for analyzing sports postures and providing feedback to athletes. Existing sport-specific systems embed bespoke human pose attributes and thus can be hard to scale for new attributes, especially for…
Human pose analysis is presently dominated by deep convolutional networks trained with extensive manual annotations of joint locations and beyond. To avoid the need for expensive labeling, we exploit spatiotemporal relations in training…
Dense flow visualization is a popular visualization paradigm. Traditionally, the various models and methods in this area use a continuous formulation, resting upon the solid foundation of functional analysis. In this work, we examine a…
This paper summarizes the recent progress in human motion analysis and its applications. In the beginning, we reviewed the motion capture systems and the representation model of human's motion data. Next, we sketched the advanced human…