It takes the average reader 5 hours and 7 minutes to read Emotion Recognition from Eye Region Signals Using Local Binary Patterns by Gaurav Jain
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Automated facial expression analysis for Emotion Recognition (ER) is an active research area towards creating socially intelligent systems. The eye region, often considered integral for ER by psychologists and neuroscientists, has received very little attention in engineering and computer sciences. Using eye region as an input signal presents several benefits for low-cost, non-intrusive ER applications.In the second proposed framework, a color-based approach to ER from the eye region is explored using Local Color Vector Binary Patterns (LCVBP). LCVBP extend the traditional LBP by incorporating color information extracting a rich and a highly discriminative feature set, thereby providing promising results.This work proposes two frameworks towards ER from eye region images. The first framework uses Local Binary Patterns (LBP) as the feature extractor on grayscale eye region images. The results validate the eye region as a significant contributor towards communicating the emotion in the face by achieving high person-dependent accuracy. The system is also able to generalize well across different environment conditions.
Emotion Recognition from Eye Region Signals Using Local Binary Patterns by Gaurav Jain is 298 pages long, and a total of 76,884 words.
This makes it 101% the length of the average book. It also has 94% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 7 hours to read Emotion Recognition from Eye Region Signals Using Local Binary Patterns aloud.
Emotion Recognition from Eye Region Signals Using Local Binary Patterns is suitable for students ages 12 and up.
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