{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:52:15Z","timestamp":1750308735213,"version":"3.41.0"},"reference-count":20,"publisher":"Association for Computing Machinery (ACM)","issue":"3s","license":[{"start":{"date-parts":[[2012,9,1]],"date-time":"2012-09-01T00:00:00Z","timestamp":1346457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2012,9]]},"abstract":"<jats:p>With the fast-growing popularity of smart phones in recent years, augmented reality (AR) on mobile devices is gaining more attention and becomes more demanding than ever before. However, the limited processors in mobile devices are not quite promising for AR applications that require real-time processing speed. The challenge exists due to the fact that, while fast features are usually not robust enough in matchings, robust features like SIFT or SURF are not computationally efficient. There is always a tradeoff between robustness and efficiency and it seems that we have to sacrifice one for the other. While this is true for most existing features, researchers have been working on designing new features with both robustness and efficiency. In this article, we are not trying to present a completely new feature. Instead, we propose an efficient matching method for robust features. An adaptive scoring scheme and a more distinctive descriptor are also proposed for performance improvements. Besides, we have developed an outdoor augmented reality system that is based on our proposed methods. The system demonstrates that not only it can achieve robust matchings efficiently, it is also capable to handle large occlusions such as passengers and moving vehicles, which is another challenge for many AR applications.<\/jats:p>","DOI":"10.1145\/2348816.2348826","type":"journal-article","created":{"date-parts":[[2012,10,15]],"date-time":"2012-10-15T17:13:12Z","timestamp":1350321192000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Efficient matchings and mobile augmented reality"],"prefix":"10.1145","volume":"8","author":[{"given":"Wei","family":"Guan","sequence":"first","affiliation":[{"name":"University of Southern California, Los Angeles, CA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suya","family":"You","sequence":"additional","affiliation":[{"name":"University of Southern California, Los Angeles, CA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ulrich","family":"Newmann","sequence":"additional","affiliation":[{"name":"University of Southern California, Los Angeles, CA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2012,10,16]]},"reference":[{"volume-title":"Proceedings of the International Conference on Computer Vision (ICCV).","author":"Agarwal S.","key":"e_1_2_1_1_1","unstructured":"Agarwal , S. , Snavely , N. , Simon , I. , Seitz , S. , and Szeliski , R . 2009. Building rome in a day . In Proceedings of the International Conference on Computer Vision (ICCV). Agarwal, S., Snavely, N., Simon, I., Seitz, S., and Szeliski, R. 2009. Building rome in a day. In Proceedings of the International Conference on Computer Vision (ICCV)."},{"volume-title":"Proceedings of the EEE\/RSJ International Conference on Intelligent Robots and Systems (IROS).","author":"Azad P.","key":"e_1_2_1_2_1","unstructured":"Azad , P. , Asfour , T. , and Dillmann , R . 2009. Combining harris interest points and the sift descriptor for fast scale-invariant object recognition . In Proceedings of the EEE\/RSJ International Conference on Intelligent Robots and Systems (IROS). Azad, P., Asfour, T., and Dillmann, R. 2009. Combining harris interest points and the sift descriptor for fast scale-invariant object recognition. In Proceedings of the EEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2007.09.014"},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Boykov Y.","key":"e_1_2_1_4_1","unstructured":"Boykov , Y. and Huttenlocher , D . 2000. Daptive bayesian recognition in tracking rigid objects . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Boykov, Y. and Huttenlocher, D. 2000. Daptive bayesian recognition in tracking rigid objects. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Cham T.","key":"e_1_2_1_5_1","unstructured":"Cham , T. and Rehg , J . 1999. A multiple hypothesis approach to figure tracking . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Cham, T. and Rehg, J. 1999. A multiple hypothesis approach to figure tracking. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Chen Y.","key":"e_1_2_1_6_1","unstructured":"Chen , Y. , Rui , Y. , and Huang , T . 2001. JPDAF-based HMM for real-time contour tracking . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Chen, Y., Rui, Y., and Huang, T. 2001. JPDAF-based HMM for real-time contour tracking. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"volume-title":"Proceedings of the Workshop on Mobile Interaction with the Real World.","author":"Henze N.","key":"e_1_2_1_7_1","unstructured":"Henze , N. , Schinke , T. , and Boll , S . 2009. What is that&quest; Object recognition from natural features on a mobile phone . In Proceedings of the Workshop on Mobile Interaction with the Real World. Henze, N., Schinke, T., and Boll, S. 2009. What is that&quest; Object recognition from natural features on a mobile phone. In Proceedings of the Workshop on Mobile Interaction with the Real World."},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008078328650"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.173"},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Li B.","key":"e_1_2_1_10_1","unstructured":"Li , B. and Chellappa , R . 2000. Simultaneous tracking and verification via sequential posterior estimation . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Li, B. and Chellappa, R. 2000. Simultaneous tracking and verification via sequential posterior estimation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"volume-title":"Proceedings of the IEEE Workshop Applications of Computer Vision.","author":"Lipton A.","key":"e_1_2_1_11_1","unstructured":"Lipton , A. , Fujiyoshi , H. , and Patil , R . 1998. Moving target classification and tracking from real-time video . In Proceedings of the IEEE Workshop Applications of Computer Vision. Lipton, A., Fujiyoshi, H., and Patil, R. 1998. Moving target classification and tracking from real-time video. In Proceedings of the IEEE Workshop Applications of Computer Vision."},{"key":"e_1_2_1_12_1","volume-title":"Proceedings of the 7th International Conference on Computer Vision (ICCV).","author":"Lowe D.","year":"1999","unstructured":"Lowe , D. 1999 . Object recognition from local scaleinvariant features . In Proceedings of the 7th International Conference on Computer Vision (ICCV). Lowe, D. 1999. Object recognition from local scaleinvariant features. In Proceedings of the 7th International Conference on Computer Vision (ICCV)."},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Rosales R.","key":"e_1_2_1_13_1","unstructured":"Rosales , R. and Sclaroff , S . 1999. 3D trajectory recovery for tracking multiple objects and trajectory guided recognition of actions . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Rosales, R. and Sclaroff, S. 1999. 3D trajectory recovery for tracking multiple objects and trajectory guided recognition of actions. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"volume-title":"Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). 2051--2058","author":"Se S.","key":"e_1_2_1_14_1","unstructured":"Se , S. , Lowe , D. , and Little , J . 2001. Vision-based mobile robot localization and mapping using scale-invariant features . In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). 2051--2058 . Se, S., Lowe, D., and Little, J. 2001. Vision-based mobile robot localization and mapping using scale-invariant features. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). 2051--2058."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1460096.1460165"},{"volume-title":"Proceedings of the European Conference on Mobile Robots (ECMR).","author":"Tamimi H.","key":"e_1_2_1_16_1","unstructured":"Tamimi , H. , Andreasson , H. , Treptow , A. , Duckett , T. , and Zell , A . 2005. Localization of mobile robots with omnidirectional vision using particle filter and iterative sift . In Proceedings of the European Conference on Mobile Robots (ECMR). Tamimi, H., Andreasson, H., Treptow, A., Duckett, T., and Zell, A. 2005. Localization of mobile robots with omnidirectional vision using particle filter and iterative sift. In Proceedings of the European Conference on Mobile Robots (ECMR)."},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISMAR.2008.4637338"},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Wang L.","key":"e_1_2_1_18_1","unstructured":"Wang , L. and Neumann , U . 2009. A robust approach for automatic registration of aerial images with untextured aerial LIDAR data . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Wang, L. and Neumann, U. 2009. A robust approach for automatic registration of aerial images with untextured aerial LIDAR data. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"volume-title":"Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).","author":"Wolf J.","key":"e_1_2_1_19_1","unstructured":"Wolf , J. , Burgard , W. , and Burkhardt , H . 2002. Robust vision-based localization for mobile robots using an image retrieval system based on invariant features . In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). Wolf, J., Burgard, W., and Burkhardt, H. 2002. Robust vision-based localization for mobile robots using an image retrieval system based on invariant features. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)."},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Zhou Q.","key":"e_1_2_1_20_1","unstructured":"Zhou , Q. and Neumann , U . 2009. A streaming framework for seamless building reconstruction from large-scale aerial LIDAR data . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Zhou, Q. and Neumann, U. 2009. A streaming framework for seamless building reconstruction from large-scale aerial LIDAR data. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."}],"container-title":["ACM Transactions on Multimedia Computing, Communications, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2348816.2348826","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2348816.2348826","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T20:22:02Z","timestamp":1750278122000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2348816.2348826"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,9]]},"references-count":20,"journal-issue":{"issue":"3s","published-print":{"date-parts":[[2012,9]]}},"alternative-id":["10.1145\/2348816.2348826"],"URL":"https:\/\/doi.org\/10.1145\/2348816.2348826","relation":{},"ISSN":["1551-6857","1551-6865"],"issn-type":[{"type":"print","value":"1551-6857"},{"type":"electronic","value":"1551-6865"}],"subject":[],"published":{"date-parts":[[2012,9]]},"assertion":[{"value":"2012-01-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2012-05-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2012-10-16","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}