Application of Face Recognition Methods for Process Automation in Intelligent Meeting Room

Author(s):  
Alexander Ronzhin
2020 ◽  
Vol 3 (2) ◽  
pp. 175-181
Author(s):  
Suwarno Suwarno

The purpose of this research is to build a face recognition system, and implement it into an RPA (Robotic Process Automation) software to expand automation capabilities. The system is built using the Python programming language. The face recognition algorithm that is used is an open-source library that has been pre-trained and developed beforehand along with a library called OpenCV. The client side of the system is desktop based, and requires a stable internet connection. Users of the system are able to register faces into the system, and then later detect and extract information from them using only images of faces with an average speed of 500 ms for every frame, with an accuracy of ~98% with tolerance set at the default value of 0.6. The system is also capable of automatically registering any new faces that it encounters.


2010 ◽  
Vol 69 (3) ◽  
pp. 161-167 ◽  
Author(s):  
Jisien Yang ◽  
Adrian Schwaninger

Configural processing has been considered the major contributor to the face inversion effect (FIE) in face recognition. However, most researchers have only obtained the FIE with one specific ratio of configural alteration. It remains unclear whether the ratio of configural alteration itself can mediate the occurrence of the FIE. We aimed to clarify this issue by manipulating the configural information parametrically using six different ratios, ranging from 4% to 24%. Participants were asked to judge whether a pair of faces were entirely identical or different. The paired faces that were to be compared were presented either simultaneously (Experiment 1) or sequentially (Experiment 2). Both experiments revealed that the FIE was observed only when the ratio of configural alteration was in the intermediate range. These results indicate that even though the FIE has been frequently adopted as an index to examine the underlying mechanism of face processing, the emergence of the FIE is not robust with any configural alteration but dependent on the ratio of configural alteration.


Author(s):  
Chrisanthi Nega

Abstract. Four experiments were conducted investigating the effect of size congruency on facial recognition memory, measured by remember, know and guess responses. Different study times were employed, that is extremely short (300 and 700 ms), short (1,000 ms), and long times (5,000 ms). With the short study time (1,000 ms) size congruency occurred in knowing. With the long study time the effect of size congruency occurred in remembering. These results support the distinctiveness/fluency account of remembering and knowing as well as the memory systems account, since the size congruency effect that occurred in knowing under conditions that facilitated perceptual fluency also occurred independently in remembering under conditions that facilitated elaborative encoding. They do not support the idea that remember and know responses reflect differences in trace strength.


2014 ◽  
Author(s):  
Mario Baldassari ◽  
Justin Kantner ◽  
D. Stephen Lindsay
Keyword(s):  

2010 ◽  
Author(s):  
Margaret Tsai ◽  
Jennifer Groscup
Keyword(s):  

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