Abstract
In this paper, we propose a building detection algorithm for video based navigation system which overlays driving directions on the captured video from in-vehicle camera. We used edge segments of small size blocks within an image frame to remove background objects, trees, etc. Search range determination and edge tracing technique were also developed to determine the building area as the final step. The experiments show 88.9 % detection rate on the average and 95.9% for navigation video without trees and signs. The proposed algorithm can be also applied to point-of-interest (POI) detection for location based services (LBS) in ubiquitous computing environment.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 544-551 |
| Number of pages | 8 |
| Volume | 4352 LNCS |
| Edition | PART 2 |
| DOIs | |
| Publication status | Published - 2007 Dec 1 |
| Externally published | Yes |
| Event | 13th International Multimedia Modeling Conference, MMM 2007 - Singapore, Singapore Duration: 2007 Jan 9 → 2007 Jan 12 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Number | PART 2 |
| Volume | 4352 LNCS |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 13th International Multimedia Modeling Conference, MMM 2007 |
|---|---|
| Country | Singapore |
| City | Singapore |
| Period | 07/1/9 → 07/1/12 |
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Keywords
- Augmented reality
- Building detection
- Building recognition
- Navigation
- Telematics
ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science
Cite this
Building detection in augmented reality based navigation system. / Lee, Kisung; Kim, Yongkwon; Cho, Seong Ik; Choi, Kyungho.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4352 LNCS PART 2. ed. 2007. p. 544-551 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4352 LNCS, No. PART 2).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Building detection in augmented reality based navigation system
AU - Lee, Kisung
AU - Kim, Yongkwon
AU - Cho, Seong Ik
AU - Choi, Kyungho
PY - 2007/12/1
Y1 - 2007/12/1
N2 - In this paper, we propose a building detection algorithm for video based navigation system which overlays driving directions on the captured video from in-vehicle camera. We used edge segments of small size blocks within an image frame to remove background objects, trees, etc. Search range determination and edge tracing technique were also developed to determine the building area as the final step. The experiments show 88.9 % detection rate on the average and 95.9% for navigation video without trees and signs. The proposed algorithm can be also applied to point-of-interest (POI) detection for location based services (LBS) in ubiquitous computing environment.
AB - In this paper, we propose a building detection algorithm for video based navigation system which overlays driving directions on the captured video from in-vehicle camera. We used edge segments of small size blocks within an image frame to remove background objects, trees, etc. Search range determination and edge tracing technique were also developed to determine the building area as the final step. The experiments show 88.9 % detection rate on the average and 95.9% for navigation video without trees and signs. The proposed algorithm can be also applied to point-of-interest (POI) detection for location based services (LBS) in ubiquitous computing environment.
KW - Augmented reality
KW - Building detection
KW - Building recognition
KW - Navigation
KW - Telematics
UR - http://www.scopus.com/inward/record.url?scp=77149137861&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77149137861&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-69429-8_57
DO - 10.1007/978-3-540-69429-8_57
M3 - Conference contribution
AN - SCOPUS:77149137861
SN - 9783540694281
VL - 4352 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 544
EP - 551
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -