Recent empirical and theoretical work suggests that visual features such as color and orientation can be stored or retrieved independently in visual working memory (VWM), even in cases when they belong to the same object. Yet it remains unclear whether different feature dimensions have their own capacity limits, or whether they compete for shared but limited resources in VWM. In 3 experiments, participants memorized arrays of dual-feature objects, for which the number of feature values was fixed on one feature dimension and was varied on the other feature dimension. The results show that memory performance on the fixed dimension was not affected by the number of to-be-stored feature values on the other. These findings provide converging evidence that visual features can be encoded and stored separately in VWM if the task requires it, with each having its own capacity limit and little cross-dimensional interference. (PsycINFO Database Record

Drowsiness poses a serious challenge to road safety and various in-cabin sensing technologies have been experimented with to monitor driver alertness. Cameras offer a convenient means for contactless sensing, but they may violate user privacy and require complex algorithms to accommodate user (e.g., sunglasses) and environmental (e.g., lighting conditions) constraints. This paper presents a lightweight convolution neural network that measures eye closure based on eye images captured by a wearable glass prototype, which features a hot mirror-based design that allows the camera to be installed on the glass temples. The experimental results showed that the wearable glass prototype, with the neural network in its core, was highly effective in detecting eye blinks. The blink rate derived from the glass output was highly consistent with an industrial gold standard EyeLink eye-tracker. As eye blink characteristics are sensitive measures of driver drowsiness, the glass prototype and the lightweight neural network presented in this paper would provide a computationally efficient yet viable solution for real-world applications.