To survive the competition, companies always think about having the best employees. The selection is depended on the answers to the questions of the interviewer and the behavior of the candidate during the interview session. The study of this behavior is always based on a psychological analysis of the movements accompanying the answers and discussions. Few techniques are proposed until today to analyze automatically candidate’s non-verbal behavior. This paper is a part of a work psychology recognition system; it concentrates on spontaneous hand gesture which is very significant in interviews according to psychologists. We propose motion history representation of hand based on a hybrid approach that merges optical flow and history motion images. The optical flow technique is used firstly to detect hand motions in each frame of a video sequence. Secondly, we use the history motion images (HMI) to accumulate the output of the optical flow in order to have finally a good representation of the hand‘s local movement in a global temporal template.
Khalifa, I., Ejbali, R., Zaied, M. (2018). Hand motion modeling for psychology analysis in job interview using Optical Flow-History Motion Image (OF-HMI). In 10th International Conference on Machine Vision, ICMV 2017 [10.1117/12.2314841].
Hand motion modeling for psychology analysis in job interview using Optical Flow-History Motion Image (OF-HMI)
KHALIFA, I
;
2018
Abstract
To survive the competition, companies always think about having the best employees. The selection is depended on the answers to the questions of the interviewer and the behavior of the candidate during the interview session. The study of this behavior is always based on a psychological analysis of the movements accompanying the answers and discussions. Few techniques are proposed until today to analyze automatically candidate’s non-verbal behavior. This paper is a part of a work psychology recognition system; it concentrates on spontaneous hand gesture which is very significant in interviews according to psychologists. We propose motion history representation of hand based on a hybrid approach that merges optical flow and history motion images. The optical flow technique is used firstly to detect hand motions in each frame of a video sequence. Secondly, we use the history motion images (HMI) to accumulate the output of the optical flow in order to have finally a good representation of the hand‘s local movement in a global temporal template.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.