Projects per year
Activity recognition is an essential objective of a smart building system which responds to what is happening in a scene. In this paper, a view invariant activity recognition system is proposed to recognise human actions. Selection of applicable features is made and solutions are proposed to deal with probable challenges including differing views on actions and directionality issues. This paper explores a number of features that can be utilised in action recognition systems and chooses suitable features to mitigate the challenges properly. Motion History Image (MHI) based on historical appearance information is used in combination with local motion vectors which are computed through each iteration sequence of the MHI information using an optical flow algorithm. A multi-view dataset (MuHaVi) and a single view dataset (Weizmann) are used to demonstrate and validate the proposed method. Our method, can detect a wide range of actions in multi-view scenarios and shows competitive performance in comparison with state-of-the-art action classification techniques.
|Title of host publication||IET 3rd International Conference on Intelligent Signal Processing (ISP 2017)|
|Place of Publication||London, UK|
|Publisher||IET Conference Publications|
|Number of pages||6|
|Publication status||Published - 21 May 2018|
|Event||IET 3rd International Conference on Intelligent Signal Processing (ISP 2017) - Savoy Place, IET Headquarters, London, United Kingdom|
Duration: 4 Dec 2017 → 5 Dec 2017
Conference number: 3
|Conference||IET 3rd International Conference on Intelligent Signal Processing (ISP 2017)|
|Abbreviated title||IET ISP 2017|
|Period||4/12/17 → 5/12/17|
- Motion History Image
- Optical Flow
FingerprintDive into the research topics of 'Appearance and motion information based human activity recognition'. Together they form a unique fingerprint.
Multiscale Feature Descriptors and Extraction
Chiverton, J., Sanders, D. & Vuksanovic, B.
20/04/16 → …
2D and 3D Voxel based Feature Extraction
Chiverton, J., Vuksanovic, B. & Sanders, D.
20/04/16 → …
Device Independent Human Activity Recognition
Chiverton, J., Ndzi, D., Yang, L. & Al-Faris, M.
8/03/17 → 2/09/19