1,721,011 research outputs found
Fast real-time segmentation and tracking of multiple subjects by time-of-flight camera: A new approach for real-time multimedia applications with 3D camera sensor
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Leyenes: A gaze-based text entry method using linear smooth pursuit and target speed
No full textGaze-based writing is one of the most widespread eye tracking applications for human–computer interaction. While eye tracking communication has traditionally been employed as an assistive technology, declining prices of eye trackers now make it a feasible alternative to keyboards or touchscreens in many contexts (for example, the interaction with public info points). In this paper we propose Leyenes, a text entry method based on smooth pursuit, a natural eye movement that occurs when the gaze follows a moving target. Our approach requires no explicit calibration by the user, allowing for more spontaneous interaction and enabling eye input even when calibration is difficult to achieve or maintain. To the best of our knowledge, Leyenes is the first text entry technique based on smooth pursuit that considers both (approximate) gaze speed and position and employs a linear interface instead of the more common circular layouts. The results of the user study we conducted show that the proposed solution is slow but robust, with a very low error rate, which makes it particularly suitable for extemporaneous writing of short text
GazeScale: Towards General Gaze-Based Interaction in Public Places
No full textGaze-based interaction has until now been almost an exclusive prerogative of the assistive field, as it is considered not sufficiently performing compared to traditional communication methods based on keyboards, pointing devices, and touch screens. However, situations such as the one we are experiencing now due to the COVID-19 pandemic highlight the importance of touchless communication, to minimize the spread of the disease. In this paper, as an example of the potential pervasive use of eye tracking technology in public contexts, we propose and study five interfaces for a gaze-controlled scale, to be used in supermarkets to weigh fruits and vegetables. Given the great heterogeneity of potential users, the interaction must be as simple and intuitive as possible and occur without the need for calibration. The experiments carried out confirm that this goal is achievable and show strengths and weaknesses of the five interfaces
Gaze-Based Human–Computer Interaction for Museums and Exhibitions: Technologies, Applications and Future Perspectives
No full textEye tracking technology is now mature enough to be exploited in various areas of human–computer interaction. In this paper, we consider the use of gaze-based communication in museums and exhibitions, to make the visitor experience more engaging and attractive. While immersive and interactive technologies are now relatively widespread in museums, the use of gaze interaction is still in its infancy—despite the benefits it could provide, for example, to visitors with motor disabilities. Apart from some pioneering early works, only the last few years have seen an increase in gaze-based museum applications. This literature review aims to discuss the state of the art on this topic, highlighting advantages, limitations and current and future trends
Automatic selection of regions of interest in a video by a depth-color image matting
No full textThe automatic detection of regions of interest in a video is fundamental for a fast generation of many ground truth images. In this paper we introduce a new solution for selecting regions of interest based on an automatic image matting method. Image matting is a set of techniques designed to obtain a precise separation of background and foreground in image or video sequences. Basically all the matting approaches need a direct human interaction, there are only few total automatic solutions. To achieve this goal we combine two different video streams: the color one and the depth one. In particular, we use an automatic depth based segmentation to substitute the human input in the Soft Scissors, one of the most precise matting algorithm. The overall efficiency is achieved using the Nvidia CUDA architecture to execute the most computational intensive sections of algorithm. The result of the matting can be used as a ground truth for successive elaborations
D-Care: A Multi-Tone LLM-Based Chatbot Assistant for Diabetes Patients
No full textDiabetes is a common chronic illness projected to increase significantly in the coming years. Managing diabetes is complex, requiring patients to frequently adjust their treatments and lifestyles to prevent complications. Awareness and adherence to healthy habits are thus essential. Artificial Intelligence (AI) can assist in this effort. Recent advancements in Large Language Models (LLMs) have enabled the creation of effective chatbots to support patients. However, despite their growing use, there are still a few formal user studies on LLMs for diabetes patients. This study aims to investigate the ability of an LLM-based chatbot to provide useful and understandable information to potential patients. Specifically, the goal was to examine how variations in language and wording affect the comprehension and perceived usability of the chatbot. To this end, D-Care, a chatbot assistant based on OpenAI’s ChatGPT-4o, was developed. D-Care can generate answers in four different tones of voice, ranging from elementary to technical language. A user study with 40 participants showed that changes in tone can indeed impact the system’s comprehension and usability
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