Please use this identifier to cite or link to this item: http://oaps.umac.mo/handle/10692.1/165
Title: Indoor Navigation by Image Recognition
Authors: HONG, KA WO (熊家和)
Department: Department of Computer and Information Science
Faculty: Faculty of Science and Technology
Issue Date: 2017
Citation: HONG, K. W. (2017). Indoor Navigation by Image Recognition (Outstanding Academic Papers by Students (OAPS)). Retrieved from University of Macau, Outstanding Academic Papers by Students Repository.
Abstract: Image recognition technology has become increasingly popular in daily life since smartphones are also increasingly powerful. The purpose of smartphone is no longer limited to communication, but also entertainment, computation, etc. Navigation is one of the major usage of smartphone. Global Positioning System (GPS) is widely used in the outdoor environment for navigation. However, GPS signal is strongly influenced in indoor environment and hence not applicable. Many researchers have proposed various alternative positioning methods. For instance, a fusion approach combining Wi-Fi and Dead Reckoning technique, and an approach using infrared technique. Nevertheless, these methods still have some limitations, such as heavy computation and practical difficulties. In addition, we realized that digital navigation system provides better and clearer location information than paper map. Positioning system is not enough for practical use. Hence, these factors motivate me to design an indoor navigation system using image recognition. In this paper, we propose a method of an indoor navigation that is implemented on smartphone .The method uses the indoor environment features to locate user’s location and a route calculating algorithm to generate an appropriate path for user. Users can know the direction indicated by a visual image immediately after the path is generated. The proposed method does not requires pre-installed tag or marker and hence its cost is much lower.
Instructor: Prof. PUN, CHI MAN
Programme: Bachelor of Science in Computer Science
URI: http://oaps.umac.mo/handle/10692.1/165
Appears in Collections:FST OAPS 2017

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