Showing papers by "Andrew C. Gallagher published in 2016"

Where do emotions come from? Predicting the Emotion Stimuli Map

Abstract: Which parts of an image evoke emotions in an observer? To answer this question, we introduce a novel problem in computer vision — predicting an Emotion Stimuli Map (ESM), which describes pixel-wise contribution to evoked emotions. Building a new image database, EmotionROI, as a benchmark for predicting the ESM, we find that the regions selected by saliency and objectness detection do not correctly predict the image regions which evoke emotion. Although objects represent important regions for evoking emotion, parts of the background are also important. Based on this fact, we propose using fully convolutional networks for predicting the ESM. Both qualitative and quantitative experimental results confirm that our method can predict the regions which evoke emotion better than both saliency and objectness detection.

Systems and methods for dynamically scoring implicit user interaction

Abstract: A method of dynamically scoring implicit interactions can include receiving, by an interaction analysis server from an imaging system, a plurality of images of an environment captured in a period of time corresponding to display of a presentation, retrieving, by the interaction analysis server, content information corresponding to content of the presentation, and identifying, by a presence detector of the interaction analysis server, that a face appears in at least one image of the plurality of images. The method can further include matching, by a facial recognition system of the interaction analysis server, the face with a user identifier, retrieving, by a client device information retriever, client device information associated with the user identifier and corresponding to the period of time, and calculating, by a client device interaction score calculator, a client device interaction score based on one or more correspondences between the client device information and the content information.