Face recognition๐Ÿ”—

Eocortex allows to use several modules that perform face recognition using a database: Face Recognition (Complete), Face Recognition (Light) and Unique Visitor Counting.

However, it is not possible to use Face Recognition (Light) module with otherface recognition modules on one camera at the same time.

The modules ensure high recognition accuracy and can be used together with access control systems at the facilities with high security requirements, for example, at banks or restricted access facilities. Another important use of the modules can be automatic identification of the hotel guests, restaurant customers, and the visitors of other similar enterprises.

Comparison of modules

Capabilities

Versions

Face Recognition (Light)

Face Recognition (Complete)

Unique Visitor Counting

Identification of faces contained in a database

โˆš

โˆš

โ€“

Identification of people wearing sunglasses, headgear, etc.

โ€“

โˆš

โˆš

Relative recognition accuracy

Medium

High

โ€“

Number of people in database

Up to 500

Unlimited

โ€“

Determination of sex and age

โ€“

โˆš

โˆš

Recognition of emotions

โ€“

โˆš

โˆš

Recognition of faces in archive

โ€“

โˆš

โ€“

Reports regarding faces

โˆš

โˆš

Detection only

Reports regarding unique visitors

โ€“

โ€“

โˆš

Usage of high-performance video card (GPU)

+

โˆš

โˆš

Usage of several video cards (GPUs)

โ€“

โˆš

โˆš

โˆš

Yes

โ€“

No

+

Optionally

Details

Face Recognition (Complete) and Unique Visitor Counting modules use all the suitable video cards installed on the server. Every camera with the recognition module enabled is assigned to one of the cards.

When the number of cameras with the recognition modules enabled exceeds the quantity of video cards used, the cameras will be uniformly distributed among the video cards, as applicable, without considering the characteristics of the video streams coming from the cameras and the performance of the video cards (i.e. an equal number of cameras will be assigned to each video card, wherever possible).

Unique Visitor Counting module is intended for generating unique visitor counting reports based on detecting and recognizing faces. It is possible to exclude faces pertaining to certain groups from the counting, for example, to avoid counting employees.

The Face Recognition (Complete), Face Recognition (Light) and Unique Visitor Counting modules determine the uniqueness of a face on the basis of the set of features jointly called the โ€œindexโ€. The modules do not use individual points (dots) of faces when determining the index; instead, the image with the size of 100x100 pixels (using the โ€œpointsโ€ terminology, a face is recognized using approximately 10 thousand points). For each face located, an entry is created in the archive of the server where this face was found, even if the face has not been explicitly entered into the database. Subsequently, these events will be available for viewing in the event archive. These modules are capable of recognizing several faces present in the frame at the same time (10 or more, if the computing capacity allows it).

The Face Recognition (Complete) module can identify masked faces with high accuracy; provided that the database contains samples of these persons without a mask. Also, this module can recognize turned faces; despite the fact that only images of faces looking directly into the camera are entered into the database.

The face database may be located on the same server where the recognition is being performed, or, alternatively, on another server of a unified multiserver video surveillance system.

Each entry in the face database contains the following:

  • One or more images (screenshots and/or photographs) of a personโ€™s face;

  • Surname, first name, patronymic of a person that are entered manually and are optional;

  • Additional information (optional text box);

  • Group affiliation (optional parameter).

The uniqueness of the entries of the database is determined by the face index. Thus, the database can contain several entries with the coincident surname, first name and patronymic (including the empty field).

It is possible to work with the face database from the Eocortex Client application, or using the API.

Compatibility with other modules (Complete)

OS

Requires Eocortex motion detector

Neural networks

Compatible with modules

Incompatible with modules

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Standard

Special

โˆš

โˆš

โˆš

โˆš

โˆš

  • Abandoned object detection module

  • Auto zoom

  • Counting people in queue

  • Crowd monitoring

  • Emergency vehicle detection

  • Face detection

  • Face Mask Detector

  • Fire and smoke detector

  • Frame area blurring

  • License Plate Recognition (Complete)

  • License Plate Recognition (Light)

  • Loud sound detection

  • People counting

  • Personnel activity monitoring

  • Sabotage detector

  • Search for objects

  • Shelf Fullness Check

  • Traffic density heat map

  • Tracking

  • Uniform Detector

  • Unique Visitor Counting

  • Face Recognition (Light)

  • Fisheye dewarping module

  • Object Classification and Counting

1If used in combination, module selection is available to display the results of the analysis in the Eocortex Client application

โˆš

supported and required for the module to work

+

supported and provides additional features of the module

โ€“

not supported or not required for the module to work

โš 

not recommended for use with the current module

Compatibility with other modules (Light)

OS

Requires Eocortex motion detector

Neural networks

Compatible with modules

Incompatible with modules

/svg/ico-windows-os-white.svg

/svg/ico-linux-os-white.svg

Standard

Special

โˆš

โˆš

โˆš

โˆš

โˆš

  • Abandoned object detection module

  • Auto zoom

  • Counting people in queue

  • Crowd monitoring

  • Emergency vehicle detection

  • Face detection

  • Face Mask Detector

  • Fire and smoke detector

  • Frame area blurring

  • License Plate Recognition (Complete)

  • License Plate Recognition (Light)

  • Loud sound detection

  • People counting

  • Personnel activity monitoring

  • Sabotage detector

  • Search for objects

  • Shelf Fullness Check

  • Traffic density heat map

  • Tracking

  • Uniform Detector

  • Face Recognition (Complete)

  • Fisheye dewarping module

  • Object Classification and Counting

  • Unique Visitor Counting

1If used in combination, module selection is available to display the results of the analysis in the Eocortex Client application

โˆš

supported and required for the module to work

+

supported and provides additional features of the module

โ€“

not supported or not required for the module to work

โš 

not recommended for use with the current module

Use

Use of the module in the Eocortex Client application.