You are cordially invited to attend our CG Colloquium on Thursday, May 2nd, 2019, 15:45-17:45h, at Pulse Hall 4
The program features the following three speakers:
Title: Player model analysis for adaptive content delivery in an educational game
Abstract: Player in games has been a useful way for understanding player motivation, style and preferences, assisting us to predict their behaviour, adapt the and improve user experience. For serious games, learning is also an factor to consider. Most work done in this area is about adaptive difficulty. While in our educational game Squla, students are exposed to multiple game types, it’s interesting to know how their behavioural data could their game type preference, and whether custom game type delivery could improve students’ engagement and learning. Therefore we present a player analysis method game adaptation, and experiment with target student groups to look into the impact.
Title: Automatic reconstruction of real-world buildings using open data
Abstract: Using publicly available data , such as Google streetview panoramas and OpenStreetMap building, it is possible to reconstruct real-world buildings. While these are not highly detailed, they will give a general impression of a. The proposed method can quickly reconstruction an entire neighbourhood in major urban centers around the world.
Julie Hongping Feng
Title: Building a 4D MRI blood flow statistical model
Abstract: Cardiovascular (CVDs) are the global number one cause of death. Current of CVDs is mainly based on functions and morphology of cardiovascular, and 4D MRI blood flow data has become a new and powerful source of, which allows both anatomical and functional analysis in a single. However, it is still difficult to efficiently utilize this data source diagnose CVDs. One of the main reasons is the lack of standard analysis and understanding of this rather new imaging modality. The method to understand the healthy behaviour and its variation is to build an atlas. Current blood flow atlas do not support 3D velocity vector field full information. We attempt to build a 4D MRI blood flow atlas similar to statistical shape and appearance models by applying Principal Component Analysis (PCA) to get the mean and main variations of the blood flow fields. The of this atlas would help physicians understand the 4D MRI data and assist them to identify whether the data is abnormal or not. In order to more efficient representations of variations for vector fields, we also tested Complex PCA and Quaternion PCA, besides traditional Real PCA. Finally, will visualize the results such that they can be interpretable.