Outdoors augmented reality on mobile phone using loxel-based visual feature organization Export

@inproceedings{takacs08, abstract = {We have built an outdoors augmented reality system for mobile phones that matches camera-phone images against a large database of location-tagged images using a robust image retrieval algorithm. We avoid network latency by implementing the algorithm on the phone and deliver excellent performance by adapting a state-of-the-art image retrieval algorithm based on robust local descriptors. Matching is performed against a database of highly relevant features, which is continuously updated to reflect changes in the environment. We achieve fast updates and scalability by pruning of irrelevant features based on proximity to the user. By compressing and incrementally updating the features stored on the phone we make the system amenable to low-bandwidth wireless connections. We demonstrate system robustness on a dataset of location-tagged images and show a smart-phone implementation that achieves a high image matching rate while operating in near real-time.}, address = {New York, NY, USA}, author = {Takacs, Gabriel and Chandrasekhar, Vijay and Gelfand, Natasha and Xiong, Yingen and Chen, Wei C. and Bismpigiannis, Thanos and Grzeszczuk, Radek and Pulli, Kari and Girod, Bernd}, booktitle = {MIR '08: Proceeding of the 1st ACM international conference on Multimedia information retrieval}, citeulike-article-id = {3945383}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1460096.1460165}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1460096.1460165}, doi = {10.1145/1460096.1460165}, isbn = {978-1-60558-312-9}, keywords = {detection, object, onur2009}, location = {Vancouver, British Columbia, Canada}, pages = {427--434}, posted-at = {2009-06-29 19:30:03}, priority = {2}, publisher = {ACM}, title = {Outdoors augmented reality on mobile phone using loxel-based visual feature organization}, url = {http://dx.doi.org/10.1145/1460096.1460165}, year = {2008} }

TY - CONF ID - takacs08 L3 - citeulike-article-id:3945383 N2 - We have built an outdoors augmented reality system for mobile phones that matches camera-phone images against a large database of location-tagged images using a robust image retrieval algorithm. We avoid network latency by implementing the algorithm on the phone and deliver excellent performance by adapting a state-of-the-art image retrieval algorithm based on robust local descriptors. Matching is performed against a database of highly relevant features, which is continuously updated to reflect changes in the environment. We achieve fast updates and scalability by pruning of irrelevant features based on proximity to the user. By compressing and incrementally updating the features stored on the phone we make the system amenable to low-bandwidth wireless connections. We demonstrate system robustness on a dataset of location-tagged images and show a smart-phone implementation that achieves a high image matching rate while operating in near real-time. CY - Vancouver, British Columbia, Canada SN - 978-1-60558-312-9 AD - New York, NY, USA EP - 434 TI - Outdoors augmented reality on mobile phone using loxel-based visual feature organization PB - ACM T2 - MIR '08: Proceeding of the 1st ACM international conference on Multimedia information retrieval SP - 427 KW - detection KW - object KW - onur2009 AU - Takacs, Gabriel AU - Chandrasekhar, Vijay AU - Gelfand, Natasha AU - Xiong, Yingen AU - Chen, Wei AU - Bismpigiannis, Thanos AU - Grzeszczuk, Radek AU - Pulli, Kari AU - Girod, Bernd PY - 2008/// UR - http://dx.doi.org/10.1145/1460096.1460165 ER -