Using Structure from Motion Mapping to Record and Analyze Details of the Colossal Hats (<i>Pukao</i>) of Monumental Statues on Rapa Nui (Easter Island)

Hixon, Sean; Lipo, Carl P.; Hunt, Terry L.; Lee, Christopher

doi:10.1017/aap.2017.28

Cited by 14 publications

(9 citation statements)

References 90 publications

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“…UAVs and structure-from-motion (SfM) photogrammetric software have become go-to tools for monitoring hazardous locations such as landslides [6][7][8][9][10][11][12] and subsidence/sinkholes [13][14][15]. These technologies have also been widely adopted in coastal erosion [16][17][18], marine science [19][20][21], both marine and terrestrial ecology [22][23][24][25][26][27], archaeology [28][29][30][31][32][33][34][35], and civil engineering [36][37][38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Measuring Change Using Quantitative Differencing of Repeat Structure-From-Motion Photogrammetry: The Effect of Storms on Coastal Boulder Deposits

Nagle-McNaughton

Cox

2019

Remote Sensing

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Repeat photogrammetry is increasingly the go-too tool for long-term geomorphic monitoring, but quantifying the differences between structure-from-motion (SfM) models is a developing field. Volumetric differencing software (such as the open-source package CloudCompare) provides an efficient mechanism for quantifying change in landscapes. In this case study, we apply this methodology to coastal boulder deposits on Inishmore, Ireland. Storm waves are known to move these rocks, but boulder transportation and evolution of the deposits are not well documented. We used two disparate SfM data sets for this analysis. The first model was built from imagery captured in 2015 using a GoPro Hero 3+ camera (fisheye lens) and the second used 2017 imagery from a DJI FC300X camera (standard digital single-lens reflex (DSLR) camera); and we used CloudCompare to measure the differences between them. This study produced two noteworthy findings: First, volumetric differencing reveals that short-term changes in boulder deposits can be larger than expected, and that frequent monitoring can reveal not only the scale but the complexities of boulder transport in this setting. This is a valuable addition to our growing understanding of coastal boulder deposits. Second, SfM models generated by different imaging hardware can be successfully compared at sub-decimeter resolution, even when one of the camera systems has substantial lens distortion. This means that older image sets, which might not otherwise be considered of appropriate quality for co-analysis with more recent data, should not be ignored as data sources in long-term monitoring studies.Despite these improvements in protocols for data collection and analysis, quantifying change via repeat photogrammetry remains a challenge, generally requiring manipulation of digital terrain models (DTMs) using Geographic Information Systems (GIS) [45,46]. But recent innovations in 3D differencing software, as implemented in the open-source package CloudCompare (www.danielgm.net/cc/) enable rapid, objective, and replicable quantitative differencing [47]. CloudCompare is a cross-platform 3D point cloud and mesh processing package, which provides a suite of features for direct comparison of dense point clouds (>10 million points) and meshes on standard consumer computer hardware [48,49]. Accessibility and ease of use make CloudCompare an attractive tool, and it is applied increasingly in a variety of fields, including mapping [50,51], archaeology [52,53], and geomorphology [54][55][56][57].Another issue relevant to long term monitoring studies is how to deal with repeat imagery captured using different kinds of hardware, with different resolutions and/or distortion levels. The ultra-wide-angle (fisheye) lenses mounted on the popular consumer camera brand GoPro capture a~120 • field of view, but have barrel distortion due to their short focal length. Despite their limitations, GoPro cameras are popular tools for acquiring UAV imagery [24,31,[58][59][60], they are relatively inexpensive, are light enou...

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Section: Introductionmentioning

confidence: 99%

Measuring Change Using Quantitative Differencing of Repeat Structure-From-Motion Photogrammetry: The Effect of Storms on Coastal Boulder Deposits

Nagle-McNaughton

Cox

2019

Remote Sensing

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“…Rationale : To create a good SfM reconstruction, a high amount of overlap between images is required [ 9 , 11 ], which means that vertices “seen” by many cameras have a lower risk to contain noise.…”

Section: Methodsmentioning

confidence: 99%

“…Structure from Motion (SfM) is widely used for visualization and inspection purposes in the building [ 1 , 2 , 3 ], manufacturing [ 4 ] and energy industries [ 5 ], as well as for geology [ 6 , 7 , 8 ] and cultural preservation [ 9 , 10 , 11 ]. Because of the reliance of SfM on 2D image data, it is prone to geometric noise and topological defects, if optimal image capturing conditions are not met ( Figure 1 ).…”

Section: Introductionmentioning

confidence: 99%

Rough or Noisy? Metrics for Noise Estimation in SfM Reconstructions

Nikolov

Madsen

2020

Sensors

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Structure from Motion (SfM) can produce highly detailed 3D reconstructions, but distinguishing real surface roughness from reconstruction noise and geometric inaccuracies has always been a difficult problem to solve. Existing SfM commercial solutions achieve noise removal by a combination of aggressive global smoothing and the reconstructed texture for smaller details, which is a subpar solution when the results are used for surface inspection. Other noise estimation and removal algorithms do not take advantage of all the additional data connected with SfM. We propose a number of geometrical and statistical metrics for noise assessment, based on both the reconstructed object and the capturing camera setup. We test the correlation of each of the metrics to the presence of noise on reconstructed surfaces and demonstrate that classical supervised learning methods, trained with these metrics can be used to distinguish between noise and roughness with an accuracy above 85%, with an additional 5–6% performance coming from the capturing setup metrics. Our proposed solution can easily be integrated into existing SfM workflows as it does not require more image data or additional sensors. Finally, as part of the testing we create an image dataset for SfM from a number of objects with varying shapes and sizes, which are available online together with ground truth annotations.

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“…Archaeologists are also realizing the analytical and illustrative promise of geographic information systems (GIS) and drone photogrammetry, employing them in tandem to systematically map architecture, model terrain, and examine relationships between spatial variables (Hixon et al. ; Howland et al. ; for GIS and remote survey, see Franklin and Hammer ; Green and Petrie ).…”

Section: Methodological and Epistemological Advancesmentioning

confidence: 99%

New Digs: Networks, Assemblages, and the Dissolution of Binary Categories in Anthropological Archaeology

Kosiba

2019

American Anthropologist

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Anthropological archaeology has long been a process of categorization. The history of the subdiscipline could be rendered in terms of an ongoing project to create, critique, and then refashion the categories by which archaeologists understand and explain social and ecological processes. Despite ever-changing theoretical tides, many archaeologists have continued to adhere to a lingua franca that demarcates their object of study, whether "the past," "nature," complexity, material culture, or historical knowledge. In 2018, strong currents in archaeological scholarship have both challenged and washed out the boundaries of many of these epistemological mainstays. This was more than a postmodern exercise to question metanarratives of history or to destabilize supposed social universals. The recent scholarship develops innovative theoretical perspectives and sophisticated methodological tools to shed light on the varied human interactions, practices, and projects that were previously occluded by research too sharply focused on bounded categories such as periods, polities, adaptations, and meanings. Furthermore, archaeologists are now more than ever critically examining the colonial institutions that they perpetuate and seeking to establish new common ground with Indigenous communities. A decidedly archaeological perspective seems to be taking shape.This is a view that sees social life from the ground up in terms of complicated relationships between people, things, and other organisms that cannot be reduced to catchall categories. [year in review, archaeology, archaeological theory, current issues, Indigenous archaeology, environmental anthropology] RESUMEN La arqueología antropológica ha sido durante mucho tiempo un proceso de categorización. La historia de la subdisciplina podría ser descrita en términos de un proyecto continuo de crear, criticar y luego rehacer las categorías a través de las cuales los arqueólogos entienden y explican los procesos sociales y ecológicos. A pesar de las mareas teóricas siempre cambiantes, muchos arqueólogos han continuado adhiriéndose a una lengua franca que demarca su objeto de estudio, ya sea "el pasado", "naturaleza", complejidad, cultura material o conocimiento histórico.En 2018, corrientes fuertes en la investigación arqueológica han tanto retado como difuminado los límites de muchos de los pilares epistemológicos. Esto fue más que un ejercicio posmoderno para cuestionar metanarrativas de la historia o para desestabilizar supuestos universales sociales. La reciente investigación desarrolla perspectivas teóricas innovadoras y herramientas metodológicas sofisticadas para arrojar luz sobre las variadas interacciones humanas, prácticas y proyectos que estuvieron previamente ocluidos por investigación excesivamente enfocada en categorías delimitadas tales como períodos, unidades políticas, adaptaciones y significados. Además, los arqueólogos ahora están más que nunca examinando críticamente las instituciones coloniales que perpetúan y buscando establecer un nuevo terreno común con las c...

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Using Structure from Motion Mapping to Record and Analyze Details of the Colossal Hats (Pukao) of Monumental Statues on Rapa Nui (Easter Island)

Cited by 14 publications

References 90 publications

Measuring Change Using Quantitative Differencing of Repeat Structure-From-Motion Photogrammetry: The Effect of Storms on Coastal Boulder Deposits

Measuring Change Using Quantitative Differencing of Repeat Structure-From-Motion Photogrammetry: The Effect of Storms on Coastal Boulder Deposits

Rough or Noisy? Metrics for Noise Estimation in SfM Reconstructions

New Digs: Networks, Assemblages, and the Dissolution of Binary Categories in Anthropological Archaeology

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