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We present MoCaPose, a novel wearable motion capturing (MoCap) approach to continuously track the wearer's upper body's dynamic poses through multi-channel capacitive sensing integrated in fashionable, loose-fitting jackets. Unlike conventional wearable ...
Many patients with neurological disorders, such as Ataxia, do not have easy access to neurologists, -especially those living in remote localities and developing/underdeveloped countries. Ataxia is a degenerative disease of the nervous system that ...
Imagine a near-future smart home. Home-embedded visual AI sensors continuously monitor the resident, inferring her activities and internal states that enable higher-level services. Here, as home-embedded sensors passively monitor a free person, good ...
End-to-end deep learning models are increasingly applied to safety-critical human activity recognition (HAR) applications, e.g., healthcare monitoring and smart home control, to reduce developer burden and increase the performance and robustness of ...
Although deep learning holds the promise of novel and impactful interfaces, realizing such promise in practice remains a challenge: since dataset-driven deep-learned models assume a one-time human input, there is no recourse when they do not understand ...
Socially Interactive Agents (SIAs) offer users with interactive face-to-face conversations. They can take the role of a speaker and communicate verbally and nonverbally their intentions and emotional states; but they should also act as active listener ...
Humans have internal models of robots (like their physical capabilities), the world (like what will happen next), and their tasks (like a preferred goal). However, human internal models are not always perfect: for example, it is easy to underestimate a ...
For successful deployment of robots in multifaceted situations, an understanding of the robot for its environment is indispensable. With advancing performance of state-of-the-art object detectors, the capability of robots to detect objects within their ...
Despite the growing literature on human attitudes toward robots, particularly prosocial behavior, little is known about how robots' perspective-taking, the capacity to perceive and understand the world from other viewpoints, could influence such ...
Recent research in robot learning suggests that implicit human feedback is a low-cost approach to improving robot behavior without the typical teaching burden on users. Because implicit feedback can be difficult to interpret, though, we study different ...
An interesting application for social robots is to act as a presenter, for example as a museum guide. In this paper, we present a fully automated system architecture for building adaptive presentations for embodied agents. The presentation is generated ...
In recent studies, pre-trained models and pseudo data have been key factors in improving the performance of the English grammatical error correction (GEC) task. However, few studies have examined the role of pre-trained models and pseudo data in the ...
Freehand interaction enhances user experience, allowing one to use bare hands to manipulate virtual objects in AR. Yet, it remains challenging to accurately and efficiently detect contacts between real hand and virtual object, due to the imprecise ...
Wearable, embedded, and IoT devices are a centrepiece of many ubiquitous computing applications, such as fitness tracking, health monitoring, home security and voice assistants. By gathering user data through a variety of sensors and leveraging machine ...
Driver emotions play a vital role in driving safety and performance. Consequently, regulating driver emotions through empathic interfaces have been investigated thoroughly. However, the prerequisite - driver emotion sensing - is a challenging endeavor: ...
To secure computer infrastructure, we need to configure all security-relevant settings. We need security experts to identify security-relevant settings, but this process is time-consuming and expensive. Our proposed solution uses state-of-the-art ...
Persuading people to change their opinions is a common practice in online discussion forums on topics ranging from political campaigns to relationship consultation. Enhancing people's ability to write persuasive arguments could not only practice their ...
This project creates a visual-mental-physical circuit between a Generative Adversarial Network (GAN), a co-robotic arm, and a five-year-old child. From training images to the latent space of a GAN, through pen on paper to a live human collaborator, it ...
Unwanted camera obstruction can severely degrade captured images, including both scene occluders near the camera and partial occlusions of the camera cover glass. Such occlusions can cause catastrophic failures for various scene understanding tasks such ...
Learning the spatial-temporal structure of body movements is a fundamental problem for character motion synthesis. In this work, we propose a novel neural network architecture called the Periodic Autoencoder that can learn periodic features from large ...