Related papers: Media Objects in Time - A Multimedia Streaming Sys…
Besides the classical offline setup of machine learning, stream learning constitutes a well-established setup where data arrives over time in potentially non-stationary environments. Concept drift, the phenomenon that the underlying…
Devices and sensors generate streams of data across a diversity of locations and protocols. That data usually reaches a central platform that is used to store and process the streams. Processing can be done in real time, with…
Reusable data/code and reproducible analyses are foundational to quality research. This aspect, however, is often overlooked when designing interactive stream analysis workflows for time-series data (e.g., eye-tracking data). A mechanism to…
Many real-world datasets -- from an artist's body of work to a person's social media history -- exhibit meaningful semantic changes over time that are difficult to capture with existing dimensionality reduction methods. To address this gap,…
Multimedia engages an audience through a combination of text, audio, still images, animation, video, or interactivity-based content formats. Along this vein, free platforms have been seen to allow budding enthusiasts to create multimedia…
Deep neural networks, and in particular recurrent networks, are promising candidates to control autonomous agents that interact in real-time with the physical world. However, this requires a seamless integration of temporal features into…
Live streaming, which allows streamers to broadcast their work to live viewers, is an emerging practice for teaching and learning computer programming. Participation in live streaming is growing rapidly, despite several apparent challenges,…
An increasing number of scientific applications rely on stream processing for generating timely insights from data feeds of scientific instruments, simulations, and Internet-of-Thing (IoT) sensors. The development of streaming applications…
Prior work has established Test-Time Training (TTT) as a general framework to further improve a trained model at test time. Before making a prediction on each test instance, the model is first trained on the same instance using a…
Media streaming has been adopted for a variety of applications such as entertainment, visualization, and design. Unlike video/audio streaming where the content is usually consumed sequentially, 3D applications such as gaming require…
In this paper we report on a multimedia communication system including a VCoIP (Video Conferencing over IP) software with a distributed architecture and its applications for teaching scenarios. It is a simple, ready-to-use scheme for…
We present a brief summary of current approaches and challenges in the network traffic management area. In this contribution, we well cover the most recent experiments on the network traffic and behavior of applications under various…
The prototype of a workflow system for the submission of content to a digital object repository is here presented. It is based entirely on open-source standard components and features a service-oriented architecture. The front-end consists…
With the transformation of computing from personal computers to the Internet, document formats have also seen some changes over the years. Future document formats are likely going to adapt to the emerging needs of ubiquitous computing,…
Diffusion-based methods can generate realistic images and videos, but they struggle to edit existing objects in a video while preserving their appearance over time. This prevents diffusion models from being applied to natural video editing…
In this paper, a general moving object trajectories framework is put forward to allow independent applications processing trajectories data benefit from a high level of interoperability, information sharing as well as an efficient answer…
Streaming data applications are becoming more common due to the ability of different information sources to continuously capture or produce data, such as sensors and social media. Despite recent advances, most visualization approaches, in…
Diffusion models have been widely used in time series and spatio-temporal data, enhancing generative, inferential, and downstream capabilities. These models are applied across diverse fields such as healthcare, recommendation, climate,…
Immersive 3D media is an emerging type of media that captures, encodes and reconstructs the 3D appearance of people and objects, with applications in tele-presence, teleconference, entertainment, gaming and other fields. In this paper, we…
Many well-known, real-world problems involve dynamic data which describe the relationship among the entities. Hypergraphs are powerful combinatorial structures that are frequently used to model such data. For many of today's data-centric…