scholarly journals Real-time facial expression transfer with single video camera

2016 ◽  
Vol 27 (3-4) ◽  
pp. 301-310 ◽  
Author(s):  
Shuang Liu ◽  
Xiaosong Yang ◽  
Zhao Wang ◽  
Zhidong Xiao ◽  
Jianjun Zhang
Author(s):  
S. Devi ◽  
Dr. M. Rajalakshmi ◽  
S. Saranya ◽  
B. Jeevanandan ◽  
A. Ramya

2014 ◽  
Vol 08 (02) ◽  
pp. 209-227 ◽  
Author(s):  
Håkon Kvale Stensland ◽  
Vamsidhar Reddy Gaddam ◽  
Marius Tennøe ◽  
Espen Helgedagsrud ◽  
Mikkel Næss ◽  
...  

There are many scenarios where high resolution, wide field of view video is useful. Such panorama video may be generated using camera arrays where the feeds from multiple cameras pointing at different parts of the captured area are stitched together. However, processing the different steps of a panorama video pipeline in real-time is challenging due to the high data rates and the stringent timeliness requirements. In our research, we use panorama video in a sport analysis system called Bagadus. This system is deployed at Alfheim stadium in Tromsø, and due to live usage, the video events must be generated in real-time. In this paper, we describe our real-time panorama system built using a low-cost CCD HD video camera array. We describe how we have implemented different components and evaluated alternatives. The performance results from experiments ran on commodity hardware with and without co-processors like graphics processing units (GPUs) show that the entire pipeline is able to run in real-time.


Author(s):  
Siu-Yeung Cho ◽  
Teik-Toe Teoh ◽  
Yok-Yen Nguwi

Facial expression recognition is a challenging task. A facial expression is formed by contracting or relaxing different facial muscles on human face that results in temporally deformed facial features like wide-open mouth, raising eyebrows or etc. The challenges of such system have to address with some issues. For instances, lighting condition is a very difficult problem to constraint and regulate. On the other hand, real-time processing is also a challenging problem since there are so many facial features to be extracted and processed and sometimes, conventional classifiers are not even effective in handling those features and produce good classification performance. This chapter discusses the issues on how the advanced feature selection techniques together with good classifiers can play a vital important role of real-time facial expression recognition. Several feature selection methods and classifiers are discussed and their evaluations for real-time facial expression recognition are presented in this chapter. The content of this chapter is a way to open-up a discussion about building a real-time system to read and respond to the emotions of people from facial expressions.


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