Cataloging public objects using aerial and street-level images - Urban trees

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 2016-December, Issue , 2016, Pages 6014-6023

  Wegner, Jan D ^a   Branson, Steve ^b   Hall, David ^b   Schindler, Konrad ^a   Perona, Pietro ^b  

^a ETH ZURICH   (Switzerland)

^b CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); FORESTRY; LOCATION; PATTERN RECOGNITION; STATISTICAL TESTS;

COMPUTER VISION SYSTEM; GEO-REFERENCED IMAGES; GEOGRAPHIC LOCATION; HUMAN PERFORMANCE; MULTIPLE VIEWPOINTS; OBJECT DETECTORS; PUBLIC INFRASTRUCTURES; TECHNICAL CHALLENGES;

COMPUTER VISION;

EID: 84986317228     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2016.647     Document Type: Conference Paper

References (49)

1. S. Agarwal, Y. Furukawa, N. Snavely, I. Simon, B. Curless, S. M. Seitz, and R. Szeliski. Building rome in a day. Commun. ACM, 54 (10): 105-112, 2011.
2. S. Agarwal, N. Snavely, I. Simon, S. M. Seitz, and R. Szeliski. Building Rome in a Day. In International Conference on Computer Vision, 2009.
3. D. Anguelov, C. Dulong, D. Filip, C. Frueh, S. Lafon, R. Lyon, A. Ogale, L. Vincent, and J. Weaver. Google street view: Capturing the world at street level. Computer, (6): 32-38, 2010.
4. M. Blaschko. Branch and bound strategies for non-maximal suppression in object detection. In International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, 2011.
5. T. Brandtberg. Classifying individual tree species under leafoff and leaf-on conditions using airborne lidar. ISPRS Journal of Photogrammetry and Remote Sensing, 61: 325-340, 2007.
6. M. L. Clark, D. A. Roberts, and D. B. Clark. Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales. Remote Sensing of Environment, 96: 375-398, 2005.
7. D. J. Crandall, L. Backstrom, D. Cosley, S. Suri, D. Huttenlocher, and J. Kleinberg. Inferring social ties from geographic coincidences. Proceedings of the National Academy of Sciences, 107 (52): 22436-22441, 2010.
8. D. J. Crandall, L. Backstrom, D. Huttenlocher, and J. Kleinberg. Mapping the world's photos. In Proceedings of the 18th international conference onWorld wide web, pages 761-770. ACM, 2009.
9. J.-X. Du, X.-F. Wang, and G.-J. Zhang. Leaf shape based plant species recognition. Applied Mathematics and Computation, 185: 883-893, 2007.
10. M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman. The pascal visual object classes (voc) challenge. International journal of computer vision, 88 (2): 303-338, 2010.
11. J.-M. Frahm, P. Fite-Georgel, D. Gallup, T. Johnson, R. Raguram, C. Wu, Y.-H. Jen, E. Dunn, B. Clipp, S. Lazebnik, and M. Pollefeys. Building Rome on a Cloudless Day. In European Conference on Computer Vision, pages 368-381, 2010.
12. R. Girshick. Fast r-cnn. In International Conference on Computer Vision (ICCV), 2015.
13. R. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In Computer Vision and Pattern Recognition, 2014.
14. H. Göeau, P. Bonnet, A. Joly, A. Affouard, V. Bakíc, J. Barbe, S. Dufour, S. Selmi, I. Yahiaoui, C. Vignau, D. Barthélémy, and N. Boujemaa. Pl@ntNet mobile 2014: Android port and new features. In ACM International Conference on Multimedia Retrieval, 2014.
15. H. Göeau, P. Bonnet, A. Joly, V. Bakíc, J. B. I. Yahiaoui, S. Selmi, J. Carré, D. Barthélémy, N. Boujemaa, J.-F. Molino, G. Duché, and A. Péronnet. Pl@ntNet mobile app. In ACM International Conference on Multimedia, 2013.
16. A. Golovinskiy, V. Kim, and T. Funkhouser. Shape-based Recognition of 3D Point Clouds in Urban Environments. In International Conference on Computer Vision, 2009.
17. K. Hara, S. Azenkot, M. Campbell, C. L. Bennett, V. Le, S. Pannella, R. Moore, K. Minckler, R. H. Ng, and J. E. Froehlich. Improving public transit accessibility for blind riders by crowdsourcing bus stop landmark locations with google street view: An extended analysis. ACM Transactions on Accessible Computing (TACCESS), 6 (2): 5, 2015.
18. K. Hara, V. Le, and J. Froehlich. Combining crowdsourcing and google street view to identify street-level accessibility problems. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 631-640. ACM, 2013.
19. J. Hays and A. Efros. im2GPS: estimating geographic information from a single image. In IEEE Conference on Computer Vision and Pattern Recognition, 2008.
20. J. Hays and A. A. Efros. Scene completion using millions of photographs. ACM Transactions on Graphics (TOG), 26 (3): 4, 2007.
21. V. Heikkinen, I. Korpela, T. Tokola, E. Honkavaara, and J. Parkkinen. An SVM Classification of Tree Species Radiometric Signatures Based on the Leica ADS40 Sensor. IEEE Transactions on Geoscience and Remote Sensing, 49 (11): 4539-4551, 2011.
22. J. Heinzel and B. Koch. Investigating multiple data sources for tree species classification in temperate forest and use for single tree delineation. International Journal of Applied Earth Observation and Geoinformation, 18: 101-110, 2012.
23. C. M. Kelly, J. S. Wilson, E. A. Baker, D. K. Miller, and M. Schootman. Using google street view to audit the built environment: inter-rater reliability results. Annals of Behavioral Medicine, 45 (1): 108-112, 2013.
24. I. Korpela, V. Heikkinen, E. Honkavaara, F. Rohrbach, and T. Tokola. Variation and directional anisotropy of reflectance at the crown scale-implications for tree species classification in digital aerial images. Remote Sensing of Environment, 115: 2062-2074, 2011.
25. N. Kumar, P. Belhumeur, A. Biswas, D. Jacobs, J. Kress, I. Lopez, and J. Soares. Leafsnap: A computer vision system for automatic plant species identification. In European Conference on Computer Vision, pages 502-516, 2012.
26. F. Lafarge, G. Gimel'Farb, and X. Descombes. Geometric Feature Extraction by a Multi-Marked Point Process. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32 (9): 1597-1609, 2010.
27. D. G. Leckie, F. A. Gougeon, S. Tinis, T. Nelson, C. N. Burnett, and D. Paradine. Automated tree recognition in old growth conifer stands with high resolution digital imagery. Remote Sensing of Environment, 94: 311-326, 2005.
28. D. Leung and S. Newsam. Proximate sensing: Inferring what-is-where from georeferenced photo collections. In IEEE Conference on Computer Vision and Pattern Recognition, pages 2955-2962, 2010.
29. Y. Li, D. J. Crandall, and D. P. Huttenlocher. Landmark classification in large-scale image collections. In Computer vision, 2009 IEEE 12th international conference on, pages 1957-1964. IEEE, 2009.
30. Y. Li, N. Snavely, and D. P. Huttenlocher. Location Recognition using Prioritized Feature Matching. In European Conference on Computer Vision, 2010.
31. Y. Li, N. Snavely, D. P. Huttenlocher, and P. Fua. Worldwide Pose Estimation Using 3D Point Clouds. In European Conference on Computer Vision, 2012.
32. T. Lin, Y. Cui, S. Belongie, and J. Hays. Learning deep representations for Ground-to-Aerial geolocalization. In IEEE International Conference on Computer Vision and Pattern Recognition, 2015.
33. T.-Y. Lin, S. Belongie, and J. Hays. Cross-View Image Geolocalization. In IEEE Conference on Computer Vision and Pattern Recognition, 2013.
34. A. L. Majdik, Y. Albers-Schoenberg, and D. Scaramuzza. Mav urban localization from google street view data. In Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on, pages 3979-3986. IEEE, 2013.
35. K. Matzen and N. Snavely. Scene Chronology. In European Conference on Computer Vision, 2014.
36. S. Mouine, I. Yahiaoui, and A. Verroust-Blondet. Combining Leaf Salient Points and Leaf Contour Descriptions for Plant Species Recognition. In International Conference on Image Analysis and Recognition, pages 205-214, 2013.
37. R. Pu and S. Landry. A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species. Remote Sensing of Environment, 124: 516-533, 2012.
38. S. Ren, K. He, R. Girshick, and J. Sun. Faster r-cnn: Towards real-time object detection with region proposal networks. In Advances in Neural Information Processing Systems (NIPS), 2015.
39. K. L. Roth, D. A. Roberts, P. E. Dennison, M. Alonzo, S. H. Peterson, and M. Bland. Differentiating plant species within and across diverse ecosystems with imaging spectroscopy. Remote Sensing of Environment, 167: 135-151, 2015.
40. O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. Berg, and L. Fei-Fei. Imagenet Large Scale Visual Recognition Challenge. International Journal of Computer Vision, pages 1-42, 2015.
41. J. Shotton, J. Winn, C. Rother, and A. Criminisi. Textonboost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation. In Computer Vision-ECCV 2006, pages 1-15. Springer, 2006.
42. B. Soheilian, N. Paparoditis, and B. Vallet. Detection and 3d reconstruction of traffic signs from multiple view color images. ISPRS Journal of Photogrammetry and Remote Sensing, pages 1-20, 2013.
43. Q. Sun and D. Batra. Submodboxes: Near-optimal search for a set of diverse object proposals. In Neural Information Processing Systems (NIPS), 2015.
44. C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich. Going deeper with convolutions. In IEEE Conference on Computer Vision and Pattern Recognition, 2015.
45. A. Torii, M. Havlena, and T. Pajdla. From google street view to 3d city models. In Computer vision workshops (ICCV Workshops), 2009 IEEE 12th international conference on, pages 2188-2195. IEEE, 2009.
46. J. Wang, M. Korayem, and D. J. Crandall. Observing the natural world with Flickr. In IEEE International Conference on Computer Vision Workshop, pages 452-459, 2013.
47. L. Waser, C. Ginzler, M. Kuechler, E. Baltsavias, and L. Hurni. Semi-automatic classification of tree species in different forest ecosystems by spectral and geometric variables derived from Airborne Digital Sensor (ADS40) and RC30 data. Remote Sensing of Environment, 115: 76-85, 2011.
48. L. Yang, X. Wu, E. Praun, and X. Ma. Tree detection from aerial imagery. In ACM GIS'09, 2009.
49. W. Yao, P. Krzystek, and M. Heurich. Tree species classification and estimation of stem volume and DBH based on single tree extraction by exploiting airborne full-waveform LiDAR data. Remote Sensing of Environment, 123: 368-380, 2012