Mood Perception Model for Social Robot Based on Facial and Bodily Expression Using a Hidden Markov Model
Mood Perception Model for Social Robot Based on Facial and Bodily Expression Using a Hidden Markov Model
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使用隐马尔可夫模型的基于面部和身体表达的社交机器人情绪感知模型
DOI：
10.20965/jrm.2019.p0629
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Eiji Hayashi
中科院分区：
文献类型：
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作者：
J. Inthiam;A. Mowshowitz;Eiji Hayashi
在正常的人际互动过程中，人们通常交换的不仅仅是口头上的话。情感同时以非语言信息的形式传达。在本文中，我们提出了一种新的感知情绪检测模型，旨在提高机器人的社交技能。这个模型假设1)只有两种隐藏状态(积极或消极情绪)，以及2)这些状态可以通过某些面部和身体表情来识别。采用维特比算法从可见的物理表现中预测隐藏状态。我们通过将估计结果与人类观察者产生的结果进行比较来验证该模型。比较表明，我们的模型与人类观察者的表现一样好，因此该模型可以用来提高机器人的社交技能，从而赋予它以更人性化的方式进行交互的灵活性。
In the normal course of human interaction people typically exchange more than spoken words. Emotion is conveyed at the same time in the form of nonverbal messages. In this paper, we present a new perceptual model of mood detection designed to enhance a robot’s social skill. This model assumes 1) there are only two hidden states (positive or negative mood), and 2) these states can be recognized by certain facial and bodily expressions. A Viterbi algorithm has been adopted to predict the hidden state from the visible physical manifestation. We verified the model by comparing estimated results with those produced by human observers. The comparison shows that our model performs as well as human observers, so the model could be used to enhance a robot’s social skill, thus endowing it with the flexibility to interact in a more human-oriented way.