Smile Classification

Classification of Natural and Posed Smiles by Photo-reflective Sensors Embedded with Smart Eyewear


Smile is one of the representative emotional expressions which is observed frequently in daily life and essential for various non-verbal communications. People make spontaneous smiles and intentional ones. It is important to guess properly whether a person is making smile spontaneously or intentionally to understand the meaning of smiles. In this study, we propose a smile classification system with a smart eyewear that equips photo-reflective sensors and examine whether we can distinguish two types of smiles; Natural smiles caused by funny videos and fake smiles evoked by instructions. We extract geometric features: reflection intensity distribution of sensors and temporal features in time axis. By applying Support Vector Machine, we observed 94.6% as the mean accuracy among 12 participants when we used both geometric and temporal features with user dependent training. The result suggested that we can distinguish between natural and posed smile by the sensors embedded with the smart eyewear.

笑いには可笑しさを感じて自然に生じる笑いと快感情を伴わない作り笑いが存在し,笑いの種類を識別することは日常生活を営む上で重要なスキルである.カメラや筋電計を用いて 2 種類の笑いにおける表出の差異が研究されているが,これらを日常的に利用可能な識別システムに応用するのは難しい.そこで本研究では日常的に装着可能な眼鏡型表情認識デバイスを用いて 2 種類の笑いの識別を試み, 精度を評価した.


Chisa Saito,
Katsutoshi Masai,
Maki Sugimoto


  1. 反射型光センサを用いた眼鏡型表情識別装置による作り笑いと自然な笑いの識別,インタラクション2018(ポスター発表)
  2. 反射型光センサを用いた眼鏡型表情識別装置による笑いの種類の識別, VRSJAC2018