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We analyzed the patterns of coordination between users' eye movements and mouse movements when scanning a web search results page, using data gathered from a study with 32 participants. We discovered 3 patterns of active mouse usage: following the eye vertically with the mouse, following the eye horizontally with the mouse, and using the mouse to mark a(More)
Supervised methods for learning an embedding aim to map high-dimensional images to a space in which perceptually similar observations have high measurable similarity. Most approaches rely on binary similarity, typically defined by class membership where labels are expensive to obtain and/or difficult to define. In this paper we propose crowdsourcing similar(More)
While Online Social Networks (OSNs) enable users to share photos easily, they also expose users to several privacy threats from both the OSNs and external entities. The current privacy controls on OSNs are far from adequate, resulting in inappropriate flows of information when users fail to understand their privacy settings or OSNs fail to implement(More)
We describe a method for using crowd-sourced labor to track motion and ultimately annotate gestures of humans in video. Our chosen platform for deployment, Amazon Mechanical Turk, divides labor into HITs (Human Intelligence Tasks). Given the informational density of video, our task is potentially larger than a traditional HIT that involves processing a(More)
This paper tackles the complex problem of visually matching people in similar pose but with different clothes, background, and other appearance changes. We achieve this with a novel method for learning a nonlinear embedding based on several extensions to the Neighborhood Component Analysis (NCA) framework. Our method is convolutional, enabling it to scale(More)
This paper describes the development and preliminary design of a game with a purpose that attempts to build a corpus of useful and original videos of human motion. This content is intended for use in applications of machine learning and computer vision. The game, Motion Chain, encourages users to respond to text and video prompts by recording videos with a(More)
This paper demonstrates how 3D skeletal reconstruction can be performed by using a pose-sensitive embedding technique applied to multi-view video recordings. We apply our approach to challenging low-resolution video sequences. Usually skeletal reconstruction can be only achieved with many calibrated high-resolution cameras, and only blob detection can be(More)
Dance is a dynamic art form that reflects a wide range of cultural diversity and individuality. With the advancement of motion-capture technology combined with crowd-sourcing and machine learning algorithms, we explore the complex relationship between perceived dance quality/dancer's gender and dance movements/music respectively. As a feasibility study, we(More)