Human face detection algorithm via Haar cascade classifier combined with three additional classifiers

Li, Cuimei; Qi, Zhi-Liang; Jiang, Nan; Wu, Jianhua

doi:10.1109/icemi.2017.8265863

Cited by 179 publications

(64 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Haar classifiers along with addition weak classifiers were utilized in the research by Cuimei et al [5] for detection of human face, authors yield the accuracy to be approx. 80 ISSN 1335-8243 (print) © 2019 FEI TUKE ISSN 1338-3957 (online), www.aei.tuke.sk percent in case of sole Haar classifiers, and 98 percent using their proposed solution.…”

Section: Haar Classifiersmentioning

confidence: 99%

Raspberry Pi-Based Access Control Using Face Recognition

Kainz¹,

Drozd²,

Michalko³

et al. 2020

AEI

View full text Add to dashboard Cite

The aim of the research is the proposal and experimental implementation of a solution based on Raspberry Pi that is to allow face recognition with subsequent user notification. Proposal of whole system discusses the possible negative factors that can endanger functionality of the system. Once the face is recognized or not recognized, the message is sent to the administrator and access is permitted or denied. This represents the elevated level of system hardening. The system in this research is built on histogram of oriented gradients (HOG) and neural network (NN). Testing of the software system solution has been also carried out and proves the usability with detection and recognitions rates above 90%. The implemented system may be used as a part of complex IoT (Internet of Things) security solution.

show abstract

Section: Haar Classifiersmentioning

confidence: 99%

Raspberry Pi-Based Access Control Using Face Recognition

Kainz¹,

Drozd²,

Michalko³

et al. 2020

AEI

View full text Add to dashboard Cite

show abstract

“…Since both the classifiers are pre-trained in OpenCV, all the necessary files are bundled together which will be present in /opencv/data. These files are loaded whenever any of the classifiers need to be run [1].…”

Section: Face Detecting Classifiersmentioning

confidence: 99%

“…Haar classifier is based on machine-learning approach. It consists of cascade function which will be trained from multiple face and non-face images that finally help in detecting the objects (faces) in different images [1].…”

Section: Face Detecting Classifiersmentioning

confidence: 99%

“…While a huge measure of material is currently effectively open on the Web, finding explicit data remains a troublesome undertaking. An unpracticed client may discover it alongside difficult to discover the data required; even an accomplished client may miss significant Web pages [1]. Clients looking through the World Wide Web have various choices by and by accessible to them.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Image Search Engine and Individual Profile Building

Shravya¹,

Smitha²

2019

IJIRCST

View full text Add to dashboard Cite

Look technique utilized for the content gives semantically significant outcome, however isn't a similar with regards to the scan strategy utilized for pictures. Interactive media information is being distributed on the Web at an extraordinary rate. Likewise, in this time of innovation, it is conceivable to get data about any person from web. It has turned out to be fundamental to perform picture hunt of a person to recover the comparative pictures from Web. It is even conceivable to get any kind of data about any superstar from Wikipedia and different locales. This project aims at building the Image Search Engine for recovering the pictures just as structure the profile of a person, from World Wide Web. This is finished via preparing set of pictures of an individual and after that the web crawler creeps over the connections for getting the pertinent pictures. These recovered pictures coordinate with the name entered by the client. A similar outcome is utilized to get the data and manufacture the profile of a similar individual by slithering over the connections.

show abstract

“…Then we need to extract features from it. For this, haar features [16,17].For each feature calculation, they introduced the integral images. It simplifies calculation of sum of pixels.…”

Section: Proposed Methods a Face Detectionmentioning

confidence: 99%

Smart Reconnaisance and Apprise System using Raspberry PI

Alwar¹

2018

IJRASET

View full text Add to dashboard Cite

In day today life, the security of our belonging is becoming more important. The modern surveillance is integrated with many automation technologies. In this modern world, crime has become ultra modern tool. At this point of time a lot of incident occurs like robbery, stealing unwanted entrance happens, threatening abruptly. So the security does matters in this daily life. This paper presents the monitoring and controlling of surveillance system enhanced with WI-FI (IEEE 802.11) technology. This system consists of webcam, Raspberry PI (BCM2837).In this system, webcam is used to detect the motions or to trace out the intruders and also detect fire. In case of any human movement or fire accident occurs, the webcam will capture live data in the surroundings and transmit it to authorized user through WI-FI(IEEE 802.11). Simultaneously, the buzzer alerts the nearby neighbors. The system also consist of sprayer, sprays the chloroform liquid on the intruders.

show abstract

Human face detection algorithm via Haar cascade classifier combined with three additional classifiers

Cited by 179 publications

References 6 publications

Raspberry Pi-Based Access Control Using Face Recognition

Raspberry Pi-Based Access Control Using Face Recognition

Image Search Engine and Individual Profile Building

Smart Reconnaisance and Apprise System using Raspberry PI

Contact Info

Product

Resources

About