**Author details**

*2.4.4 Expression recognition in low resolution*

*Average recognition rate over all four classifiers.*

*Types of Nonverbal Communication*

JAFFE and TFEID are portrayed in **Figure 15**.

performance decreases with lower resolution.

resolution.

**26**

**Figure 15.**

**Table 6.**

**3. Conclusions**

Resolution can have significant effect on quality of the image. High resolution images may not be available always. Applications such as surveillance applications, home monitoring, smart meeting produces low resolution videos, which makes facial expression recognition difficult [21]. Very little work has been done on low resolution images. In our experiment, we studied the performance of MLH operator

**Resolution 150 110 75 55 48 36 37 27** Chi-square 95.6 94.8 94.7 93.4 Cosine 95.3 94.1 93.9 93.6 LSSVM (R) 95.7 94.9 94.7 93.4 DA 95.9 95.5 95.3 94.4 Average 95.6 94.8 94.6 93.7

in four different resolutions: 150 110, 75 55, 48 36 and 37 27. Lowresolution images are derived by down-sampling the original images. Results on

*Recognition rate of MLH in low resolution on JAFFE (left) and TFEID (right) datasets.*

For JAFFE dataset, the average recognition rate of all four classifiers for 150 110 resolution is 95.6%, which is 1.9% higher than the recognition rate in case of 37 27 resolution, which has an average recognition rate of 93.7%. Performance degradation with lower resolution is stated in **Table 6**. Results confirm that the

It is apparent that recognition of expression becomes difficult from lowresolution images. Even for a human it gets difficult. **Table 6** shows that the performance degradation for 75 55 is 0.8% but it is as high as 1.9% for 75 55

This chapter presents preprocessing technique for face registration. Head pose angle is estimated and the head is rotated if needed to make it up-right frontal pose. Eyeballs are aligned in order to register the face. In this chapter, we have also

Mahesh Goyani Gujarat Technological University, Gujarat, India

\*Address all correspondence to: mgoyani@gmail.com

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
