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  • Mantisight Face Recognition and Image Analysis Software

Mantisight Face Recognition and Image Analysis Software

We offer object recognition, person recognition, person counting, heat mapping demographic analysis, security and personalized marketing solutions with 100% domestically-developed face recognition and image analysis software. The use of the software does not require a special camera or a computer, it can easily integrate with the existing IP cameras of the corporation. Some of the main features available in the software and sample areas are as below:

Person Identification

The persons in the image are identified by their body shape without the need to show their face.

Usage examples:

  • Displays a warning in dangerous areas which should not have human activity
  • Prevention of entrance from places where there is no security available (by jumping from the wall, passing under a barrier, climbing the windows, etc.)
  • Displays a warning when children under a certain are detected in areas where they should not be, such as pools
  • Identifying humans in disaster areas during emergencies

Person Counting

Counts the persons in a specified area of the image without needing to identify their faces.

Usage examples:

  • Getting customer statistics of stores and branches
  • Measuring the rate of visitors who turned into customers (i.e 100 people walked by the store, 50 entered, and 10 purchased something)
  • Counting people during emergency drills

Heat Map

Determines the human population density in a defined area of the image and creates a heat map based on this value.

Usage examples:

  • Defining the most-visited areas in a store and measuring the documents that are seldomly visited
  • Identifying queues forming in front of the cash register and informing the persons concerned

Age Range and Gender Analysis

Determines the age range and gender of the people in the image by using face recognition technology.

Usage examples:

  • Creating customer statistics with the age range and gender information of people who are in the stores and branches
  • Displaying customized ads based on the age range and gender information of people who are present at the area or who view digital billboards

Object Recognition

Detects the objects in the image. New objects can be defined to the system by using the deep learning method.

Usage examples:

  • The detection of objects such as suspicious bags that are in the image
  • Recognition of special objects such as helmets, gloves, badges, apolets; supervision of personnel clothing
  • Detecting dangerous objects

Plate and Vehicle Recognition

Identifies the vehicles in the image and reads their plate information.

Usage examples:

  • Opening special barriers and enabling entrance to private parking lots for system registered plates
  • Keeping the records of vehicle license plates of guest cars
  • Proper parking control
  • Directing drivers to empty parking lots
  • Smart signalization
  • Detecting direction and lane violations

Face Recognition

Detects the data of 108 points on a person’s face and carries out face recognition by comparing them with the previous data.

Usage examples:

  • Keeping the records of entrance and exit information & duration of employees
  • Informing the authorities when private customers arrive
  • Informing the relevant manager when a person in the black list enters the building
  • Notifying the authorities of persons who are not registered in the system
  • Allowing entrance only to the authorized personnel in areas that require security

Mobile Face Recognition

Recognizes the face of the person by using the camera of the mobile device.

Usage examples:

  • As an alternative login method in mobile applications
  • Can be defined as the second security step in substantial payment transactions
  • Allows to carry out banking transactions from ATMs without requiring a credit card
  • The credit cards can only be used by the person whose face is defined to the system