A Movement Data Analysis and Synthesis Tool for Museum Visitors' Behaviors

Achievement of museum guide systems, in physical and virtual worlds, providing the personalization and context awareness features requires the prior analysis and identification of visitors’ behaviors. This paper analyzes and synthesizes visitors’ behaviors in museums and art galleries by using our defined parameters. A visit time and a observation distance can be calculated by using the proposed functions. The proposed synthesis algorithm is developed and used in classification. Classifying visitor styles is simply implemented by using the average and variance of their stopover time at and distance to all exhibits as shown in this paper.