Special Issue on Statistical Machine Learning for Human Behaviour Analysis
We are glad to announce that we have launched a SI on Statistical Machine Learning for Human Behaviour Analysis to be published in Entropy. This Special Issue focuses on novel vision-based approaches, which mainly belong to broader categories, such as computer vision and machine learning. The above topics fall, mainly, under categories related to computer vision and machine learning, where the theoretical advancements and practical developments usually benefit from the contributions brought by other areas of research in the relevant domains of science and technology, which is due to the multidisciplinary nature of the task.
We solicit submissions on the following topics:
- Information theory based pattern classification
- Biometric recognition
- Multimodal human analysis
- Low resolution human activity analysis
- Face analysis
- Abnormal behaviour analysis
- Unsupervised human analysis scenarios
- 3D/4D human pose and shape estimation
- Human analysis in virtual/augmented reality
- Affective computing
- Social Signal Processing
- Personality computing
- Activity recognition
- Human tracking in wild
- Application of information-theoretic concepts for human behaviour analysis
Guest editors:
Prof. Dr. Thomas Moeslund
Prof. Dr. Sergio Escalera
Prof. Dr. Gholamreza Anbarjafari
Prof. Dr. Kamal Nasrollahi
Dr. Jun Wan
Manuscript Due: 28 February 2019
You can submit your manuscript via https://susy.mdpi.com/user/manuscripts/upload/79900a07518b1835d0ada2b71f6bf49d?journal=entropy . The format of the paper and page limits are the same as the Entropy regulations.
