Enabling Mobile Phones To Support Large-Scale Museum Guidance

Point of Interest Awareness Using Indoor Positioning With a Mobile Phone

“…The PhoneGuide system (Bruns, Brombach, Zeidler and Bimber, 2007) is a museum guidance system that uses Bluetooth emitters in each exhibit, which are identified by the user's receiver. This does not allow sufficient accuracy to differentiate individual objects located within the signal range.…”

Subobject detection through spatial relationships on mobile phones

“…Instead of keying reference numbers, as it is the case for conventional audio guides, exhibits can be automatically detected through image classification techniques. We developed an adaptive museum guidance system called PhoneGuide [11,7,4,6,5]. It utilizes the visitors' personal A visitor is taking a photo of a subobject group with his mobile phone (a).…”

“…No transmission costs for communication services are necessary. So far, we combined different techniques, such as image classification with global features [11], pervasive tracking [7], dynamic classification adaptation [4,6], and ad-hoc net-work communication [5] for achieving recognition rates in the order of 82%-92% under realistic conditions (i.e., more than one hundred objects, in real museums, with real visitors). However, up to now, PhoneGuide is only able to detect single objects -by convention, the one that is centered in the camera image.…”

A new efficient pose estimation and tracking method for personal devices : application to interaction in smart spaces

“…Smart spaces have been involved in a wide range of application fields: smart home (e.g., for remote control, energy management, environmental monitoring, elderly care (Alam, Reaz, and Ali, 2012)), smart museums (e.g., to guide visitors through an unfamiliar space and provide additional information (Bruns et al, 2007)), smart cars (e.g., to detect the drowsiness of a driver (Sahayadhas, Sundaraj, and Murugappan, 2012)), etc. An example of a smart home is illustrated in Fig.…”

“…In particular, in recent years, an attractive application area requiring accurate pose estimation is Augmented Reality (AR) (Höllerer and Feiner, 2004;You, Neumann, and Azuma, 1999;Zhou, Duh, and Billinghurst, 2008;Föckler et al, 2005;Schall et al, 2009;Gómez et al, 2013;Wagner et al, 2010;Klein and Drummond, 2004;Bruns et al, 2007;Chen, Chang, and Huang, 2014). AR has been widely explored in training, entertainment, education, and tourism (Höllerer and Feiner, 2004) to facilitate a novel way for the users to interact with their surroundings.…”