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Found 8 papers, 0 papers with code
Using Big Five Personality Model to Detect Cultural Aspects in Crowds
The use of information technology in the study of human behavior is a subject of great scientific interest.
Predicting Future Pedestrian Motion in Video Sequences using Crowd Simulation
Our method is based on Physics and heuristics and use BioCrowds as crowd simulation methodology to estimate future positions of people in video sequences.
How much do you perceive this? An analysis on perceptions of geometric features, personalities and emotions in virtual humans (Extended Version)
This work aims to evaluate people's perception regarding geometric features, personalities and emotions characteristics in virtual humans.
A Software to Detect OCC Emotion, Big-Five Personality and Hofstede Cultural Dimensions of Pedestrians from Video Sequences
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.
Detecting Personality and Emotion Traits in Crowds from Video Sequences
This paper presents a methodology to detect personality and basic emotion characteristics of crowds in video sequences.
Mitigating Bias in Facial Analysis Systems by Incorporating Label Diversity
Hence, in this work, we introduce a novel learning method that combines both subjective human-based labels and objective annotations based on mathematical definitions of facial traits.
Can we truly transfer an actor's genuine happiness to avatars? An investigation into virtual, real, posed and spontaneous faces
We intend to find differences and similarities in facial expressions between real and CG datasets, posed and spontaneous faces, and also to consider the actors' genders in the videos.
Detecting Events in Crowds Through Changes in Geometrical Dimensions of Pedestrians
We hypothesize that the detection of events in videos is correlated with significant changes in pedestrian behaviors.
