A Portable Personality Recognizer Based on Affective State Classification Using Spectral Fusion of Features
A Portable Personality Recognizer Based on Affective State Classification Using Spectral Fusion of Features
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DOI：
10.1109/taffc.2018.2828845
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发表时间：
2018-07-01
影响因子：
11.2
通讯作者：
Mitra, Pabitra
中科院分区：
文献类型：
--
作者：
Basu, Anushree;Dasgupta, Anirban;Mitra, Pabitra
在本文中，我们介绍了一个系统命名为便携式人格识别器（PPR），它分类的个性，一个人使用他/她的情感状态的转变。这部作品试图揭示一个人的情感与人格之间的潜在关系。在这里，我们训练了一个隐马尔可夫模型（HMM），其中包含可观察到的情绪状态，即快乐（H），愤怒（A），惊讶（S）和厌恶（D）以及隐藏的特征，即精神质（P），外向性（E）和神经质（N）。基于该模型，系统将人格估计为精神病、外向或神经质。它通过使用可见光和热成像相机捕捉个人的面部图像来确定人的当前情感状态。利用可见光和血流灌注热图像的融合特征进行情感分类。情绪状态的变化，观察使用训练的HMM估计的个性。拟议的硬件原型由一个Banana Pi板和一个7英寸的LCD屏幕组成，该屏幕具有热成像和可见光摄像头附加组件。该系统实现了87.145%的情感分类准确率，而个性识别的准确率为87.87%。
In this paper, we introduce a system named Portable Personality Recognizer (PPR), which classifies the personality of an individual using his/her transitions of affective states. This work attempts to reveal the latent relationship between emotions and personality of a person. Here, we train a hidden Markov model (HMM) with observable emotional states viz. Happiness (H), Anger (A), Surprise (S) and Disgust (D) and the hidden traits viz. Psychoticism (P), Extraversion (E) and Neuroticism (N). Based on the model, the system estimates the personality as Psychotic, Extravert or Neurotic. It does so by capturing the facial images of an individual using a visible and a thermal camera to decide the present affective state of the person. The emotion classification is carried out using fused eigenfeatures from the visible and blood perfused thermal images. The emotional state changes are observed using the trained HMM to estimate the personality. The proposed hardware prototype consists of a Banana Pi board with a seven inch LCD screen having a thermal and a visible camera add-ons. The system achieves an emotion classification accuracy of 87.145 percent, while an accuracy of 87.87 percent is achieved for personality recognition.