Human Depth Sensors-Based Activity Recognition Using Spatiotemporal Features and Hidden Markov Model for Smart Environments
Nowadays, advancements in depth imaging technologies have made human activity recognition (HAR) reliable without attaching optical markers or any other motion sensors to human body parts. This study presents a depth imaging-based HAR system to monitor and recognize human activities. In this work, we...
Main Authors: | Ahmad Jalal, Shaharyar Kamal, Daijin Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2016-01-01
|
Series: | Journal of Computer Networks and Communications |
Online Access: | http://dx.doi.org/10.1155/2016/8087545 |
Similar Items
-
A Depth Video-based Human Detection and Activity Recognition using Multi-features and Embedded Hidden Markov Models for Health Care Monitoring Systems
by: Ahmad Jalal, et al.
Published: (2017-08-01) -
A Depth Video Sensor-Based Life-Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments
by: Ahmad Jalal, et al.
Published: (2014-07-01) -
Accurate Physical Activity Recognition using Multidimensional Features and Markov Model for Smart Health Fitness
by: Amir Nadeem, et al.
Published: (2020-10-01) -
Automatic Recognition of Human Interaction via Hybrid Descriptors and Maximum Entropy Markov Model Using Depth Sensors
by: Ahmad Jalal, et al.
Published: (2020-07-01) -
Feature Selection for Hidden Markov Models and Hidden Semi-Markov Models
by: Stephen Adams, et al.
Published: (2016-01-01)