FRAGMENTS
Source abstract
Abstract
A large number of outstanding heritage sites and artifacts around the world are fragile assets, faced with different and continuous challenges. The loss of archaeological heritage indeed continues today at a constant pace, both due to natural disasters and human-made actions. The magnitude of the problem requires effective measures that can support the restoration activities in case of disasters. The latter, indeed, can be difficult and time-consuming, especially when dealing with the recomposition of fragmented and scattered objects. This is often a manual procedure that does not always lead to the correct identification of the numerous possible matches. The heritage science community urges for methods able to optimize the research efforts and the fragments matching reliability and speed. The proposed workflow (FRAGMENTS) introduces a fully automatic approach based on photogrammetric techniques, given a pre-disaster image is available.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: 3D Surveying and Cultural Heritage · Archaeological Research and Protection · Image Processing and 3D Reconstruction
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (53)
Show source-provided references
1. Il restauro dei frammenti del ciclo di affreschi della cappella ovetari agli eremitani
2. Basile · 2010
3. On solving 2D and 3D puzzles using curve matching. In: computer vision and pattern recognition, 2001. CVPR 2001
4. A multiscale method for the reassembly of two-dimensional fragmented objects. in: pattern Analysis and Machine Intelligence
5. Contour-shape based reconstruction of fragmented, 1600 bc wall paintings10.1109/TSP.2002.1003053 ↗
6. Fast, robust and efficient 2D pattern recognition for re-assembling fragmented images10.1016/j.patcog.2005.03.014 ↗
7. A texture based approach to reconstruction of archaeological finds
8. Multi-feature matching of fresco fragments
9. Virtual recomposition of frescos: separating fragments from the background
10. MOSAIC+: tools to assist virtual restoration10.18293/DMS2015-049 ↗
11. Reassembling fractured objects by geometric matching10.1145/1141911.1141925 ↗
12. Feature-based part retrieval for interactive 3D reassembly
13. A system for high-volume acquisition and matching of fresco fragments: reassembling Theran wall paintings10.1145/1360612.1360683 ↗
14. Pairwise matching of 3D fragments using cluster trees10.1007/s11263-007-0121-5 ↗
15. Digital anastylosis of the octagon in Ephesos10.1145/1551676.1551677 ↗
16. Semi-automatic geometry- driven reassembly of fractured archeological objects
17. Pairwise matching of 3D fragments
18. A computer- assisted constraint-based system for assembling fragmented objects
19. Fractured object reassembly via robust surface registration
20. GRAVITATE: geometric and semantic matching for cultural heritage artefacts
21. Comparative evaluation of binary features
22. An Analysis and implementation of the SURF method and its comparison to SIFT
23. A comparative study of SIFT and its variants10.2478/msr-2013-0021 ↗
24. Evaluation of feature-based methods for automated network orientation
25. A comparative evaluation of well-known feature detectors and descriptors10.18100/ijamec.60004 ↗
26. Image matching using SIFT, SURF, BRIEF and ORB: performance comparison for distorted images
27. Evaluation of interest point detectors10.1023/A:1008199403446 ↗
28. A performance evaluation of local descriptors10.1109/TPAMI.2005.188 ↗
29. The geometry and matching of lines and curves over multiple views10.1023/A:1008135310502 ↗
30. A comparison of affine region detectors10.1007/s11263-005-3848-x ↗
31. Visual mapping by a robot rover
32. A fast operator for detection and precise location of distinct points, corners and center of circular features
33. A combined edge and corner detector
34. SUSAN – a new approach to low level image processing10.1023/A:1007963824710 ↗
35. Adaptive and generic corner detection based on the accelerated segment test
36. Faster and better: a machine learning approach to corner detection10.1109/TPAMI.2008.275 ↗
37. Comparison and evaluation of feature point detectors
38. Passive 3D imaging
39. Object recognition from local scale-invariant features
40. Local feature view clustering for 3D object recognition
41. Distinctive image features from scale-invariant key-points10.1023/B:VISI.0000029664.99615.94 ↗
42. Vedaldi, 2010, http://www.vlfeat.org/. (Accessed 13 April 2020).
43. MicMac suite, https://micmac.ensg.eu/index.php/Accueil. (Accessed 13 April 2020).
44. ASIFT. A new framework for fully affine invariant image comparison10.1137/080732730 ↗
45. ASIFT, http://www.cmap.polytechnique.fr/-yu/research/ASIFT/demo.html. (Accessed 13 April 2020).
46. SURF: speeded up robust features10.1016/j.cviu.2007.09.014 ↗
47. SURF, https://www.mathworks.com/help/vision/ref/detectsurffeatures.html. (Accessed 13 April 2020).
48. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography10.1145/358669.358692 ↗
49. A probabilistic criterion to detect rigid point matches between two images and estimate the fundamental matrix10.1023/B:VISI.0000013094.38752.54 ↗
50. Hartley · 2003 · 700
51. Stylianou · 1997
52. Varnava · 2009
53. Virtual and physical recomposition of fragmented ecclesiastical frescoes using a photogrammetric approach