Activity Recognition from RGB-D Camera with 3D Local Spatio-temporal Features

2012 ◽  
Author(s):  
Yue Ming ◽  
Qiuqi Ruan ◽  
Alexander G. Hauptmann
Keyword(s):  
Activity Recognition ◽  
Temporal Features ◽  
Spatio Temporal

scholarly journals Activity Recognition for IoT Devices Using Fuzzy Spatio-Temporal Features as Environmental Sensor Fusion

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3512 ◽  
Author(s):  
Miguel Ángel López Medina ◽  
Macarena Espinilla ◽  
Cristiano Paggeti ◽  
Javier Medina Quero
Keyword(s):  
Fuzzy Logic ◽  
Activity Recognition ◽  
Heterogeneous Sensors ◽  
Temporal Features ◽  
Constant Change ◽  
Environmental Sensor ◽  
Spatio Temporal ◽  
Iot Devices ◽  
The University

The IoT describes a development field where new approaches and trends are in constant change. In this scenario, new devices and sensors are offering higher precision in everyday life in an increasingly less invasive way. In this work, we propose the use of spatial-temporal features by means of fuzzy logic as a general descriptor for heterogeneous sensors. This fuzzy sensor representation is highly efficient and enables devices with low computing power to develop learning and evaluation tasks in activity recognition using light and efficient classifiers. To show the methodology’s potential in real applications, we deploy an intelligent environment where new UWB location devices, inertial objects, wearable devices, and binary sensors are connected with each other and describe daily human activities. We then apply the proposed fuzzy logic-based methodology to obtain spatial-temporal features to fuse the data from the heterogeneous sensor devices. A case study developed in the UJAmISmart Lab of the University of Jaen (Jaen, Spain) shows the encouraging performance of the methodology when recognizing the activity of an inhabitant using efficient classifiers.

Fire Detection Based on Fractal Analysis and Spatio-Temporal Features

2021 ◽  
Author(s):  
Monir Torabian ◽  
Hossein Pourghassem ◽  
Homayoun Mahdavi-Nasab
Keyword(s):  
Fractal Analysis ◽  
Fire Detection ◽  
Temporal Features ◽  
Spatio Temporal

Kinematic Adaptive Frequency Sampling Combined Spatio Temporal Features for Snow Monitoring in Aerospace Applications

2021 ◽  
pp. 115472
Author(s):  
Parameshwaran Ramalingam ◽  
Lakshminarayanan Gopalakrishnan ◽  
Manikandan Ramachandran ◽  
Rizwan Patan
Keyword(s):  
Aerospace Applications ◽  
Temporal Features ◽  
Frequency Sampling ◽  
Spatio Temporal
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