Abstract

Behavioral Signal Processing aims at automating behavioral coding schemes such as those prevalent in psychology and mental health research. This paper describes a method to automatically quantify the approach-and-avoidance (AA) behavior, described by ordinal labels manually assigned by experts using either video-only or video-with-audio. We propose a novel ordinal regression (OR) algorithm and its hidden Markov model (HMM) extension for estimation of AA labels from visual motion capture based and acoustic features. The proposed algorithm transforms the OR to multiple binary classification problems, solves them by independent score-outputting classifiers and fits the cumulative logit logistic regression model with proportional odds (CLLRMP) to vectors of the classifier scores. The time series extension treats labels as states of the HMM with a likelihood function derived from the probabilistic CLLRMP …

Date

May 22, 2011

Authors

Viktor Rozgić, Bo Xiao, Athanasios Katsamanis, Brian Baucom, Panayiotis G Georgiou, Shrikanth Narayanan

Conference

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Pages

2368-2371

Publisher

IEEE