题目：Grasses, Scrubs, Trees and Random Forests plus Humans in the Loop
- Automatic habitat classification based on digital photos
讲者：Dr. Guoping Qiu, School of Computer Science,The University of Nottingham, United Kingdom
Abstract. The classification of habitats is important for developing our understanding of the natural world and for monitoring the environment and biodiversity. Traditionally, habitat classification is performed by human surveyors ─ a laborious, expensive and subjective process. In this talk, I will present our recent research in developing automatic habitat classification solutions based on digital photos. We treat habitat classification as an image-labeling problem and have developed a framework that uses a random forest to automatically label a digital photo with the habitat classes it contain. As automatic visual recognition is still very hard whilst humans can perform visual recognition with the greatest ease, we have developed a human in the loop approach to fusing high-level knowledge with low-level visual features. We take advantage of the Internet technology and employ crowd-sourcing to harvest human intelligence in a natural and effortless way. I will show experimental results to illustrate the feasibility and challenges of automatically classifying habitats with digital photos taken on the ground, the possibility of acquiring human intelligence using Internet technology, and the benefits of fusing high-level knowledge with low-level features for visual recognition. For research purposes, a manually annotated habitat digital photo database containing over 3000 high-resolution images is downloadable from http://cvl.cs.nott.ac.uk/resources/habitat3k/. This is a joint work with Dr. Mercedes Torres.
Brief Bio. Guoping Qiu is Professor (Chair) of Visual Information Processing in the School of Computer Science at the University of Nottingham, Nottingham, UK. His research interests include image processing, pattern recognition, multimedia processing, machine learning and their applications to real world problems including habitat classification, digital pathology, content-based image retrieval and automatic image tagging. He has particular expertise in high dynamic range (HDR) imaging and has developed several highly successfully techniques that are now routinely used in many digital photography software and smartphone camera apps. He has published over 170 papers in these areas and holds several European and US patents. He has won several prizes including a best paper award at the 18th International Conference on Pattern Recognition (ICPR2006). He has taught in universities in the UK and Hong Kong and consulted for multinational companies in Europe, Hong Kong and China. Recently, he took up a secondment to the University of Nottingham’s China campus where he is leading the School of Computer Science and the International Doctoral Training Centre (IDIC), a £17 million investment venture to train PhD students in the areas of new energy technologies and digital economy. His current research projects include building a high dynamic range video camera and a 3D digital microscope. He and his students are working on automatic traffic video analysis, video based crowd detection and people tracking, near duplicate image and video discovery, video summarization and their applications to smart city development amongst others.