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Over the past few years, the concept of VR has attracted increasing interest thanks to its extensive industrial and commercial applications. Currently, the 3D models of the virtual scenes are generally stored in the VR visor itself, which…
There are over a hundred virtual reality (VR) locomotion techniques that exist today, with new ones being designed as VR technology evolves. The different ways of controlling locomotion techniques (e.g., gestures, button inputs, body…
Facial expressions of emotion are a major channel in our daily communications, and it has been subject of intense research in recent years. To automatically infer facial expressions, convolutional neural network based approaches has become…
Advances in machine learning and contactless sensors have enabled the understanding complex human behaviors in a healthcare setting. In particular, several deep learning systems have been introduced to enable comprehensive analysis of…
Applying image processing algorithms independently to each frame of a video often leads to undesired inconsistent results over time. Developing temporally consistent video-based extensions, however, requires domain knowledge for individual…
Emotion detection is a crucial component of Games User Research (GUR), as it allows game developers to gain insights into players' emotional experiences and tailor their games accordingly. However, detecting emotions in Virtual Reality (VR)…
Visual-vestibular conflicts (VVCs) are a primary contributor to visually induced motion sickness (VIMS) in head-mounted displays (HMDs). However, virtual reality (VR) comfort studies often rely on exposing seated or standing users to…
Spatially dense self-supervised learning is a rapidly growing problem domain with promising applications for unsupervised segmentation and pretraining for dense downstream tasks. Despite the abundance of temporal data in the form of videos,…
Virtual Reality (VR) interfaces are increasingly used as remote visualization media in telerobotics. Remote environments captured through RGB-D cameras and visualized using VR interfaces can enhance operators' situational awareness and…
The unprecedented surge in video data production in recent years necessitates efficient tools to extract meaningful frames from videos for downstream tasks. Long-term temporal reasoning is a key desideratum for frame retrieval systems.…
Video super-resolution (VSR) is a prominent research topic in low-level computer vision, where deep learning technologies have played a significant role. The rapid progress in deep learning and its applications in VSR has led to a…
Virtual reality (VR) conferencing has the potential to provide geographically dispersed users with an immersive environment, enabling rich social interactions and user experience using avatars. However, remote communication in VR inevitably…
Purpose: In this paper, we present a novel approach for online object tracking in laparoscopic cholecystectomy (LC) surgical videos, targeting localisation and tracking of critical anatomical structures and instruments. Our method addresses…
Virtual Reality (VR) is inaccessible to blind people. While research has investigated many techniques to enhance VR accessibility, they require additional developer effort to integrate. As such, most mainstream VR apps remain inaccessible…
Adaptive Virtual Reality (VR) systems have the potential to enhance training and learning experiences by dynamically responding to users' cognitive states. This research investigates how eye tracking and heart rate variability (HRV) can be…
Do video-text transformers learn to model temporal relationships across frames? Despite their immense capacity and the abundance of multimodal training data, recent work has revealed the strong tendency of video-text models towards…
Video-Language Pre-training models have recently significantly improved various multi-modal downstream tasks. Previous dominant works mainly adopt contrastive learning to achieve global feature alignment across modalities. However, the…
This chapter aims to aid the development of Cyber-Physical Systems (CPS) in automated understanding of events and activities in various applications of video-surveillance. These events are mostly captured by drones, CCTVs or novice and…
Achieving a high level of immersion and adaptation in virtual reality (VR) requires precise measurement and representation of user state. While extrinsic physical characteristics such as locomotion and pose can be accurately tracked in…
Semi-supervised video action recognition tends to enable deep neural networks to achieve remarkable performance even with very limited labeled data. However, existing methods are mainly transferred from current image-based methods (e.g.,…