Visualization on Agglomerative Information Bottleneck Based Trajectory Clustering
Fan Yang, Qing Xu, Yuejun Guo, Sheng Liang · 2015
Undoubtedly, visualization of the trajectory clustering outputs is very important and some researches have been done on visualization of the clustering results. Still importantly, the research on visualizing the procedure of clustering, which is also of great value, is little touched. In this paper, we propose a novel 3D visualization tool, which comprehensively illustrates the Agglomerative Information Bottleneck (AIB) based clustering scheme, to help users understand the clustering approach vividly and clearly. The point of the proposed metaphor makes use of the visualization, together with rich interactions, to demonstrate the iterative clustering procedure, the corresponding results and the clustering results. The experiment demonstrates the effectiveness of our 3D visualization tool for trajectory analysis.