Human action recognition using yolo v7 algorithm

YEAR :2023

Description

In the past few years, there has been a lot of research on recognizing human actions in video analytics. However, the majority of these techniques analyze a video as a whole or classify each frame before assigning a single action label to the movie. However, it may be inferred that when contrasted with human eyesight, we (humans) just need a single instance of visual information to recognize a scene. It comes out that only a tiny collection of frames, or even just one, from the video, is sufficient for accurate recognition. Using frames from an ongoing stream of footage that can be received from a security camera, we offer a method in this study for almost real-time detection, localization, and recognition of events of interest. After a predetermined amount of time, the model accepts input frames and can assign an action label based on one frame. We estimated the action label for the stream of video by combining findings over a particular period of time. We illustrate demonstrates the YOLO approach is efficient and reasonably quick for localization and recognition in the Human Activities dataset.

ADDITIONAL INFORMATION

HARDWARE REQUIREMENTS
•System : Dual core.
•Hard Disk : 40 GB.
•Floppy Drive : 1.44 Mb.
•Monitor : 15 VGA Colour.
•Mouse : Logitech.
•Ram : 4 GB.

SOFTWARE REQUIREMENTS

•Operating system : Windows XP/7/10/11.
•Coding Language : JAVA
•Data Base : MYSQL

Reviews

There are no reviews yet.

Be the first to review “Human action recognition using yolo v7 algorithm”

Your email address will not be published. Required fields are marked *

Product Enquiry

Contact Us

Contact Us
Close