智能情绪检测

智能情绪监测

#研究发现#【智能情绪检测】面部识别软件监测个人情感初步测试已有94%的成功率。研究表示,准确细分各种情绪,通过1)开发算法,准确定义人脸特征2)分析面部特定位置和形状3)将这些特性与情绪状态联系判定情绪等三步来进行情感描绘。这个研究有效弥补了人类与机器间缺失的环节,增强人机交互,助力人工智能。

Computerized emotion detector

September 16, 2014

Inderscience Publishers

Face recognition software measures various parameters in a mug shot, such as the distance between the person"s eyes, the height from lip to top of their nose and various other metrics and then compares it with photos of people in the database that have been tagged with a given name. Now, new research looks to take that one step further in recognizing the emotion portrayed by a face.

Dev Drume Agrawal, Shiv Ram Dubey and Anand Singh Jalal of the GLAUniversity, in Mathura, Uttar Pradesh, India, suggest that the recognition of emotions by future artificial intelligences, in the form of computers or robots, will provide a missing link between the human and machine environments without which appropriate interactions between the two domains may never be entirely successful. The team has taken a three-phase approach to a software emotion detector. The first involves developing an algorithm that can precisely identify and define the features of the human face. The second then analyses the particular positions and shapes of the face. The third phase then associates those features with a person"s emotional state to decide whether they are happy, sad, angry, surprised, fearful or disgusted. Preliminary tests gave a 94 percent success rate the team reports.

While Mehrabian"s 1960s notion that half of human communication is non-verbal has been debunked several times, there remains the fact that facial expressions and body language do convey a lot of information about a person"s thoughts and emotional state. Such information, if it could be interpreted by a computer would allow us to enhance human-computer interactions. Imagine, whimsically, that one"s laptop or smart phone could change the background image or shuffle your music based on whether you had a happy or sad expression. In a more serious setting, the recognition of anger, pent-up aggression, or fear at airport screening might allow suspicious individuals to be channeled sooner rather than later to the security office while those with nothing to hide would be funneled through to the usual physical checks with less delay.

"Our experimental results suggest that the introduced method is able to support more accurate classification of emotion classification from images of faces," the team says. They add that additional refinements to the classification algorithms will improve their emotion detector still further.


Story Source:

The above story is based on materials provided by Inderscience PublishersNote: Materials may be edited for content and length.


Journal Reference:

  1. Agrawal, D.D., Dubey, S.R. and Jalal, A.S. Emotion recognition from facial expressions based on multi-level classificationInt. J. Computational Vision and Robotics, 2014, Vol. 4, No. 4, pp.365

来源:Sciencedaily

链接:http://www.sciencedaily.com/releases/2014/09/140916141535.htm


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