Paul Schrater

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Object perception has been a subject of extensive fMRI studies in recent years. Yet the nature of the cortical representation of objects in the human brain remains controversial. Analyses of fMRI data have traditionally focused on the activation of individual voxels associated with presentation of various stimuli. The current analysis approaches functional(More)
The ability of the human brain to learn is exceptional. Yet, learning is typically quite specific to the exact task used during training, a limiting factor for practical applications such as rehabilitation, workforce training, or education. The possibility of identifying training regimens that have a broad enough impact to transfer to a variety of tasks is(More)
We develop a normative statistical approach to exploratory behavior called information foraging. Information foraging highlights the specific processes that contribute to active, rather than passive, exploration and learning. We hypothesize that the hippocampus plays a critical role in active exploration through directed information foraging by supporting a(More)
How to compute initially unknown reward values makes up one of the key problems in reinforcement learning theory, with two basic approaches being used. Model-free algorithms rely on the accumulation of substantial amounts of experience to compute the value of actions, whereas in model-based learning, the agent seeks to learn the generative process for(More)
Accurate tracking is a difficult task in most computer vision applications. Errors in target localization and tracking result not only from the general uncontrolled nature of the environment but also from inaccurate modeling of the target motion. This work presents a novel solution for the robust estimation of target trajectories obtained from real-world(More)
This paper presents two different learning methods applied to the task of driver activity monitoring. The goal of the methods is to detect periods of driver activity that are not safe, such as talking on a cellular telephone, eating, or adjusting the dashboard radio system. The system presented here uses a side-mounted camera looking at a driver's profile(More)
Automatic event detection from video sequences has applications in several areas such as automatic visual surveillance, traffic monitoring for intelligent transportation systems, key frame detection for video compression, and virtual reality applications. In this work, we present a computer vision-based approach for event detection and data collection at(More)
A single glance at your crowded desk is enough to locate your favorite cup. But finding an unfamiliar object requires more effort. This superiority in recognition performance for learned objects has at least two possible sources. For familiar objects observers might: 1) select more informative image locations upon which to fixate their eyes, or 2) extract(More)
One of the primary goals of motion analysis is to accurately track the movement of objects in the environment. We report on a novel illusion in which two objects moving with identical physical velocities have different perceived velocities, creating an apparent offset in their relative spatial positions. The stimulus is a smaller object composed of a static(More)
While it is widely recognized that thinking is somehow costly, involving cognitive effort and producing mental fatigue, these costs have alternatively been assumed to exist, treated as the brain's assessment of lost opportunities, or suggested to be metabolic but with implausible biological bases. We present a model of cognitive cost based on the novel idea(More)