Face recognition in Service robotics: Analysis of the padding effect according to people age / Reconhecimento facial em robótica de serviço: análise do efeito de preenchimento de acordo com a idade das pessoas

Service robots usually perform repetitive tasks such as collecting garbage, cleaning the house, among others. This kind of robot needs different skills to perform its daily tasks, being people´s recognition a critical skill. One of the techniques used to improve face recognition is padding. The padding technique increases, by a given scale factor, the bounding box of a detected face. In previous work, we had presented a comparative analysis of the influence of the padding in the algorithm used for face recognition. This paper extends the previous analysis by considering the effect of various padding scale factors among different life stages (i.e., toddler, children, teenager, adult, senior, and golden oldie). The result of this analysis shows that increasing the bounding box of detected faces is less efficient for middle-aged people than for younger and elderly people.

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Comparative Analysis of various Illumination Normalization Techniques for Face Recognition

International Journal of Computer Applications ◽

10.5120/3419-4771 ◽

2011 ◽

Vol 28 (9) ◽

pp. 1-7 ◽

Cited By ~ 3

Author(s):

Tripti Goel ◽

Vijay Nehra ◽

Virendra P.Vishwakarma

Keyword(s):

Face Recognition ◽

Comparative Analysis ◽

Illumination Normalization

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Real Time Face Recognition based Smart Lab for Energy Conservation

Webology ◽

10.14704/web/v18si02/web18010 ◽

2021 ◽

Vol 18 (SI02) ◽

pp. 32-41

Author(s):

M. Karthikeyan ◽

T.S. Subashini ◽

M.S. Prashanth

Keyword(s):

Face Recognition ◽

Object Identification ◽

Home Automation ◽

Human Beings ◽

Environmentally Conscious ◽

Repetitive Tasks ◽

Automation Systems ◽

The Face ◽

Identification Technique ◽

Haar Cascade

Home automation offers a good solution to help conserve our natural resources in a time when we are all becoming more environmentally conscious. Home automation systems can reduce power consumption and when they are not in use automatically turn off lights and appliances. With home automation, many repetitive tasks can be performed automatically or with fewer steps. For example, each time the person gets out of his computer desk, for instance, the fan and the lights need to be turned off and switched on when he comes back to the computer desk. This is a repetitive task, and failure to do so leads to a waste of energy. This paper proposes a security/energy saving system based on face recognition to monitor the fan and lights depending on the presence or absence of the authenticated user. Initially, the authenticated faces/users LBPH (Local Binary Pattern Histogram) features were extracted and modelled using SVM to construct the face profile of all authenticated users. The webcam catches the user's picture before the PC and the Haar-cascade classifier, a profound learning object identification technique is used to identify face objects from the background. The facial recognition techniques were implemented with python and linked to the cloud environment of Ada-Fruit in order to enable or disable the light and fan on the desk. The relay status is transmitted from Ada Fruit Cloud to Arduino Esp8266 using the MQTT Protocol. If the unidentified user in the webcam is detected by this device, the information in the cloud will be set to ' off ' status, allowing light and fan to be switched off. Although Passive Infrared Sensor (PIR) is widely used in home automation systems, PIR sensors detect heat traces in a room, so they are not very sensitive when the room itself is hot. Therefore, in some countries such as INDIA, PIR sensors are unable to detect human beings in the summer. This system is an alternative to commonly used PIR sensors in the home automation process.

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