Provided is an emotion estimating apparatus capable of precisely estimating an emotion and mental state of a measurement subject by using a non-contact pulse detection technology. The emotion estimating apparatus forcibly performs re-sampling processing of digital biometric data generated by converting a heart rate signal to digital data after extracting data for one cycle at an RR interval, and obtains coefficients of harmonic components by a DCT conversion processing unit. From the coefficients of the harmonic components, AC components are removed by LPFs, whereby a coefficient data array is obtained. The coefficient data array is compared to a dictionary data group, in which dictionary data is a characteristic quantity indicating an emotion or mental state, and a similarity therebetween is calculated, whereby an emotion or mental state of a subject is estimated on the basis of the heart rate signal of the subject.
