Affective labeling of multimedia content can be useful in recommender systems. In this paper we compare the effect of implicit and explicit affective labeling in an image recommender system. The implicit affective labeling method is based on an emotion detection technique that takes as input the video sequences of the users’ facial expressions. It extracts Gabor low level features from the vide...

Natural scenes provide important affective cues for observers to avoid danger. From an adaptationist perspective, such cues affect the behavior of the observer and shape the evolution of the observer's response. It is evolutionarily significant for individuals to extract affective information from the environment as quickly and as efficiently as possible. However, the nearly endless variations ...

In college classrooms, large quantities of digital-media data showing students’ affective behaviors are continuously captured by cameras on a daily basis. To provide a bench mark for affect recognition using these big data collections, in this paper we propose the first large-scale spontaneous and multimodal student affect database. All videos in our database were selected from daily big data r...

Recent advances in the research area of affective computing have broadened the range of application areas of its findings, and additionally, as the state of the art advances in affective computing, other related research areas (computer vision, pattern recognition, etc.) discover new challenges that are related to image and video processing related to the task of automatic affective analysis. A...

Even though extracting the semantic content of information is a critical feature in information search, today’s Web sites still have poor capabilities in this regard, especially when it comes to multimedia data. While most Web sites provide visual, and sometimes, auditory content, they don’t provide any tools to process the resulting subjective information, and by doing so, they fail to support...

This paper reports our experiments for TRECVID 2010 task: Semantic Indexing. We present two approaches namely, Affective and Holistic. In the first approach, we have used combination of affective features from image, video and audio trained with neural network algorithm. Image features employed are color histogram and face detection from the keyframe. The number of face is also used in one of t...

Body image distress or body dissatisfaction is one of the most common consequences of obesity and overweight. We investigated the neural bases of body image processing in overweight and average weight young women to understand whether brain regions that were previously found to be involved in processing self-reflective, perspective and affective components of body image would show different act...