uxSense: Supporting User Experience Analysis with Visualization and Computer Vision

Andrea Batch, Yipeng Ji, Mingming Fan, Jian Zhao, Niklas Elmqvist

Room: 109

2023-10-26T03:36:00ZGMT-0600Change your timezone on the schedule page
Exemplar figure, described by caption below
An interface with a video playback component at the top left, a transcript in the top middle, and an annotations table at the top right. The bottom half of the screen is a collection of timeline visualizations.
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Visualization;visual analytics;evaluation;video analytics;machine learning;deep learning;computer vision


Analyzing user behavior from usability evaluation can be a challenging and time-consuming task, especially as the number of participants and the scale and complexity of the evaluation grows. We propose uxSense, a visual analytics system using machine learning methods to extract user behavior from audio and video recordings as parallel time-stamped data streams. Our implementation draws on pattern recognition, computer vision, natural language processing, and machine learning to extract user sentiment, actions, posture, spoken words, and other features from such recordings. These streams are visualized as parallel timelines in a web-based front-end, enabling the researcher to search, filter, and annotate data across time and space. We present the results of a user study involving professional UX researchers evaluating user data using uxSense. In fact, we used uxSense itself to evaluate their sessions.