Monitoring Intake Gestures using Sensor Fusion (Microsoft Kinect and Inertial Sensors) for Smart Hom

By Hossein Mousavi, M. Khademi, Cristina Videira Lopes. 2012

89 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Billy Pik Lik Lau
2. Marakkalage Sumudu Hasala
3. Yuren Zhou
4. Chau Yuen
5. Naveed Ul L. Hassan
6. Liliana Lo Presti
7. Marco La Cascia
8. Meng Zhang

Citations in the corpus

• A survey of data fusion in smart city applications (2019, methodology): “In hybrid computation platform, processing is distributed among two or more layers (edge, fog and cloud) as shown in [105], [110], [111].”
• A Review on Technical and Clinical Impact of Microsoft Kinect on Physical Therapy and Rehabilitation (2014, methodology): “On the other hand, systems which use depth imaging [13] may use the skeletal tracking that devices such as Microsoft Kinect or Leap Motion Sensor provide.”
• 3D skeleton-based human action classification: A survey (2016, methodology): “In [143], an inertial sensor and a depth camera are used to monitor food intake gestures (such as fi ne cutting, loading food, and maneuvering the food to the mouth).”