VGU RESEARCH REPOSITORY
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https://epub.vgu.edu.vn/handle/dlibvgu/519| Title: | Machine vision object differentiation and learning approaches | Authors: | Huynh Thanh Quan | Keywords: | Feature extraction;Neural network;Facial expression;Image database;Happy emotion | Issue Date: | 2017 | Publisher: | Vietnamese-German University | Abstract: | Computer vision has contributed and stand a big role in research study, industrial business and clinical applications in several years. Human face detection and recognition has been the remarkable features in many vision devices nowadays. Understand the different facial expressions of emotion is essential to gain insights into human cognition and perceptual. Six basic types of emotion typically seen in most cultures on over the world, such as happiness, surprise, sadness, anger, fear, and disgust. The emotion of happiness comprises the most universally general and recognized level of positive emotion. This thesis report will mark the problem to recognize and detect the happiness and unhappiness. The last previous elective report has proposed the solution to detect the human face by using Haar-like feature. Continuing with that result, I extend the face detection problem to facial expression recognition problem by using a machine learning model (neural network). A learning model has the ability to detect the happy face when the boundary of facial expression is unidentified clearly. The implementation is done by using the Matlab software. This thesis also covers the explanation of the mathematical concept as well as the implementation to solve the problem. |
URI(1): | http://epub.vgu.edu.vn/handle/dlibvgu/519 | Rights: | Attribution-NonCommercial 4.0 International |
| Appears in Collections: | Electrical Engineering and Information Technology (EEIT) |
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| Machine vision object differentiation and learning opproaches.pdf | 1.88 MB | Adobe PDF |
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