Face Recognition by Using ImageAI

  • G. Chandrakala, Dr. M. Venkatanarayana, M. Ramamurthy Naik

Abstract

Object detection refers to the capability of computer and software systems to locate objects in an image/scene and identify each object. Object detection has been widely used for face detection, vehicle detection, pedestrian counting, web images, security systems and driverless cars. Early implementations of object detection involved the use of classical algorithms, like the ones supported in OpenCV, the popular computer vision library. However, these classical algorithms could not achieve enough performance to work under different conditions. The breakthrough and rapid adoption of deep learning in 2012 brought into existence modern and highly accurate object detection algorithms and methods such as R-CNN, Fast-RCNN, Faster-RCNN, RetinaNet and fast yet highly accurate ones like SSD and YOLO. Using these methods and algorithms, based on deep learning which is also based on machine learning require lots of mathematical and deep learning frameworks understanding. There are millions of expert computer programmers and software developers that want to integrate and create new products that uses object detection. But this technology is kept out of their reach due to the extra and complicated path to understanding and making practical use it. Built ImageAI, a python library that lets programmers and software developers easily integrate state-of-the-art computer vision technologies into their existing and new applications, using just few lines of code

Published
2021-11-03
How to Cite
G. Chandrakala, Dr. M. Venkatanarayana, M. Ramamurthy Naik. (2021). Face Recognition by Using ImageAI. Design Engineering, 9837-9844. Retrieved from http://thedesignengineering.com/index.php/DE/article/view/6035
Section
Articles