Machine Learning
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Model-Based Approach for Estimating Human 3D Poses in Static Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
2005 Special Issue: The interaction of attention and emotion
Neural Networks - Special issue: Emotion and brain
2005 Special Issue: Emotion recognition in human-computer interaction
Neural Networks - Special issue: Emotion and brain
EMPATH: A Neural Network that Categorizes Facial Expressions
Journal of Cognitive Neuroscience
Applying 3D human model in a posture recognition system
Pattern Recognition Letters
Seeing Fearful Body Language Overcomes Attentional Deficits in Patients with Neglect
Journal of Cognitive Neuroscience
Robust Object Recognition with Cortex-Like Mechanisms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Designing a Posture Analysis System with Hardware Implementation
Journal of VLSI Signal Processing Systems
Responses of anterior superior temporal polysensory (stpa) neurons to “biological motion” stimuli
Journal of Cognitive Neuroscience
Improved neural network for SVM learning
IEEE Transactions on Neural Networks
Human pose recognition using chamfer distance in reduced background edge for human-robot interaction
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Spoken emotion recognition using hierarchical classifiers
Computer Speech and Language
Multiple feature extraction and hierarchical classifiers for emotions recognition
COST'09 Proceedings of the Second international conference on Development of Multimodal Interfaces: active Listening and Synchrony
Fuzzy cognitive maps for artificial emotions forecasting
Applied Soft Computing
Computer Methods and Programs in Biomedicine
Object class detection: A survey
ACM Computing Surveys (CSUR)
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Research into the visual perception of human emotion has traditionally focused on the facial expression of emotions. Recently researchers have turned to the more challenging field of emotional body language, i.e. emotion expression through body pose and motion. In this work, we approach recognition of basic emotional categories from a computational perspective. In keeping with recent computational models of the visual cortex, we construct a biologically plausible hierarchy of neural detectors, which can discriminate seven basic emotional states from static views of associated body poses. The model is evaluated against human test subjects on a recent set of stimuli manufactured for research on emotional body language.