相关论文: What Shapes Participant Data Quality? A Scoping Re…
Traditional eye tracking requires specialized hardware, which means collecting gaze data from many observers is expensive, tedious and slow. Therefore, existing saliency prediction datasets are order-of-magnitudes smaller than typical…
This paper presents a new way of getting high-quality saliency maps for video, using a cheaper alternative to eye-tracking data. We designed a mouse-contingent video viewing system which simulates the viewers' peripheral vision based on the…
Webcam eye tracking for the collection of gaze data in the context of user studies is convenient - it can be used in remote tests where participants do not need special hardware. The approach has strong limitations, especially regarding the…
Advancements in AI heavily rely on large-scale datasets meticulously curated and annotated for training. However, concerns persist regarding the transparency and context of data collection methodologies, especially when sourced through…
Knowing where people look is a useful tool in many various image and video applications. However, traditional gaze tracking hardware is expensive and requires local study participants, so acquiring gaze location data from a large number of…
Online crowdsourcing provides a scalable and inexpensive means to collect knowledge (e.g. labels) about various types of data items (e.g. text, audio, video). However, it is also known to result in large variance in the quality of recorded…
Subjective video quality assessment (VQA) is the gold standard for measuring end-user experience across communication, streaming, and UGC pipelines. Beyond high-validity lab studies, crowdsourcing offers accurate, reliable, faster, and…
Crowdsourcing enables one to leverage on the intelligence and wisdom of potentially large groups of individuals toward solving problems. Common problems approached with crowdsourcing are labeling images, translating or transcribing text,…
Crowdsourcing provides a flexible approach for leveraging human intelligence to solve large-scale problems, gaining widespread acceptance in domains like intelligent information processing, social decision-making, and crowd ideation.…
Most publicly available image quality databases have been created under highly controlled conditions by introducing graded simulated distortions onto high-quality photographs. However, images captured using typical real-world mobile camera…
Crowdsourcing has been widely used to efficiently obtain labeled datasets for supervised learning from large numbers of human resources at low cost. However, one of the technical challenges in obtaining high-quality results from…
Machine learning systems are increasingly deployed in high-stakes domains, yet they remain vulnerable to bias systematic disparities that disproportionately impact specific demographic groups. Traditional bias detection methods often depend…
Understanding human visual attention and saliency is an integral part of vision research. In this context, there is an ever-present need for fresh and diverse benchmark datasets, particularly for insight into special use cases like crowded…
This paper revisits visual saliency prediction by evaluating the recent advancements in this field such as crowd-sourced mouse tracking-based databases and contextual annotations. We pursue a critical and quantitative approach towards some…
Human visual attention is a complex phenomenon. A computational modeling of this phenomenon must take into account where people look in order to evaluate which are the salient locations (spatial distribution of the fixations), when they…
The latest developments in computer hardware, sensor technologies, and artificial intelligence can make virtual reality (VR) and virtual spaces an important part of human everyday life. Eye tracking offers not only a hands-free way of…
Crowdwork often entails tackling cognitively-demanding and time-consuming tasks. Crowdsourcing can be used for complex annotation tasks, from medical imaging to geospatial data, and such data powers sensitive applications, such as health…
Crowdsourcing information constitutes an important aspect of human-in-the-loop learning for researchers across multiple disciplines such as AI, HCI, and social science. While using crowdsourced data for subjective tasks is not new,…
User experience research often uses surveys and interviews, which may miss subconscious user interactions. This study explores eye-tracking and biometric feedback as tools to assess user engagement and cognitive load in digital interfaces.…
The subjective quality of transmitted speech is traditionally assessed in a controlled laboratory environment according to ITU-T Rec. P.800. In turn, with crowdsourcing, crowdworkers participate in a subjective online experiment using their…