Object Detection by Computer Vision

Made by Rijans Bhagat, Setu Parmar, Kushagra Saruparia

The real-time detection of humans is emerging as a significant trend with data scientists and across widespread industries from smart cities to retail to surveillance. It no longer seems like science fiction to consider:

Counting pedestrians along a path or crosswalk. Analyzing shopper behavior or dwell time. Home security cameras detect visitors or intruders. In fact, it may be easier than you think.

Successfully detecting a person in an image or video means you are building an application that will marry object detection and image classification. The tech that lets you detect objects in image data is a little different than the popular visual classification tools currently being used across many industries.

For one thing, there is now a framework in place to detect specific objects in video with varying levels of accuracy. Pairing the identified location of an object in an image with the understanding of the object’s class means your application can differentiate between a human in one region of the image versus an object that might be mistaken as a person, such as a mannequin in a retail environment.

Exploring object detection means understanding:

1. What you could accomplish by detecting people in images and video.

2. How detecting a person is different from other tech, such as facial recognition.

3. The relationship between general object detection, such as vehicle detection, and detecting people.

4. Probability issues that define these tools.

5. Current and prospective real-world industry 4.0 applications of this tech.