Human activity Recognition (HAR) are explored in video-based computer vision domain and sensor-based ubiquitous research areas. Vision-based human action or activity recognition approaches are based on RGB video sequences, or depth maps, or from skeleton data – taken from normal video cameras or depth cameras. On the other hand, sensor-based activity recognition methods are basically based on the data collected from wearable sensors having accelerometer, gyroscope, or so on. There are numerous applications on HAR, however, the healthcare, elderly support, and related applications become very important arenas with huge social and financial impact. Due to the advent of various IoT sensors, it becomes more competitive as well as easier to explore different applications. The keynote will cover HAR approaches in both video-based and sensor-based domains, highlight healthcare perspectives and methods. The presentation will be based on the 3 books as follows:
- Md Atiqur Rahman Ahad, Anindya Das Antar, Masud Ahmed, “IoT Sensor-Based Activity Recognition – Human Activity Recognition”, Springer Nature Switzerland AG, 2019.
- Md Atiqur Rahman Ahad, “Motion History Images for Action Recognition and Understanding”, Springer, 2013.
- Md Atiqur Rahman Ahad, “Computer Vision and Action Recognition: A Guide for Image Processing and Computer Vision Community for Action Understanding”, available in Springer, 2011.