Computer vision-based visitor study as a decision support system for museum

As an institution that operates within the public domain, a museum should be knowledgeable about several factors that can improve its services. One of these factors that can support the decision making for museum is visitors experiences during their visits. To gauge these collective experiences, visitor studies are conducted regularly by museums. Several visitor study approaches have been introduced, ranging from a simple field observation to sophisticated sensory devices. We proposed a new approach to monitor the behavior of museum visitors through the implementation of a computer vision software called Eyeface. The software was used to capture visitor data, including demographic information and engagement level data. These data can be used by museum to make a decision in rearranging its exhibition that can improve visitors engagement level. Additionally, the demographic data can be a basis information for museum to create particular events or promotions targeting some specific group of visitors. This approach was tested in three different museums; one was located in Edinburgh, UK while two were in Jakarta, Indonesia.