MASTER Assignment
[B][M] Recognising and understanding human activities from videos
Type: Master CS/EE/HMI/etc
Period: TBD
Student: (Unassigned)
If you are interested please contact :
Description:
Human action recognition (HAR) has a wide range of real-world applications - video surveillance systems, health monitoring, human-computer interaction, to name some. Video-based HAR is one of the most challenging tasks in computer vision. It usually entails the detection and classification of spatial-temporal behavioural patterns. Previous works in this field relied on descriptors such as skeleton trajectories, video depth, audio signals, and radar for the recognition of different human activities[1].
Objective:
In this project, the student is asked to implement a deep learning supervised framework for the recognition of a set of human activities present in videos.
- Hussain, Zawar, Quan Z. Sheng, and Wei Emma Zhang. "A review and categorization of techniques on device-free human activity recognition." Journal of Network and Computer Applications 167 (2020): 102738