  This paper presents a video analysis application to detect personality,
emotion and cultural aspects from pedestrians in video sequences, along with a
visualizer of features. The proposed model considers a series of
characteristics of the pedestrians and the crowd, such as number and size of
groups, distances, speeds, among others, and performs the mapping of these
characteristics in personalities, emotions and cultural aspects, considering
the Cultural Dimensions of Hofstede (HCD), the Big-Five Personality Model
(OCEAN) and the OCC Emotional Model. The main hypothesis is that there is a
relationship between so-called intrinsic human variables (such as emotion) and
the way people behave in space and time. The software was tested in a set of
videos from different countries and results seem promising in order to identify
these three different levels of psychological traits in the filmed sequences.
In addition, the data of the people present in the videos can be seen in a
crowd viewer.

Computer Vision and Pattern Recognition;Human-Computer Interaction