Introduction to Object Detection

 

Introduction

Object detection is in fact an advanced sub-field of computer vision in which the computer is able to recognize and find objects in images or videos. Such a technology has grown roots and is now used in many applications and has revolutionized the way we interact with both the digital and the physical worlds in a way that they are even smarter than before.

This is in contrast to image recognition, which tends on a basic level to only detect a single main object in an image, where object detection seeks to locate and identify multiple objects on the image, each of which is enclosed in a rectangular boundary box. Every object is recognized and given a score for detection reliability. An object detection network is able to filter recognizable objects out of noise by analyzing the arrangement, texture, or outline of the focal pixels inside numerous other pixels. Because of its flexibility, it was also employed in self-driving cars, medicine, shops, safety, and production, and where it still encourages new developments.

Conclusion

In the future, as AI and machine learning become better and more capable, Object detection will evolve to the next level where it can analyze moving objects real-time. This evolution promises to bring new insights and applications and wider object detection application across sectors enhancing contextual understanding of machine objects.

Reference

Towards Data Science - Object Detection Applications