Mapping by matching: a computer vision-based approach to fast and accurate georeferencing of archaeological aerial photographs

To date, aerial archaeologists generally apply simple rectification procedures or more expensive and time-consuming orthorectification algorithms to correct their aerial photographs in varying degrees for geometrical deformations induced by the topographical relief, the tilt of the camera axis and the distortion of the optics. Irrespective of the method applied, the georeferencing of the images is commonly determined with ground control points, whose measurement and identification is a time-consuming operation and often limits certain images from being accurately georeferenced. Moreover, specialised software, certain photogrammetric skills, and experience are required. Thanks to the recent advances in the fields of computer vision and photogrammetry as well as the improvements in processing power, it is currently possible to generate orthophotos of large, almost randomly collected aerial photographs in a straightforward and nearly automatic way. This paper presents a computer vision-based approach that is complemented by proven photogrammetric principles to generate orthophotos from a range of uncalibrated oblique and vertical aerial frame images. In a first phase, the method uses algorithms that automatically compute the viewpoint of each photograph as well as a sparse 3D geometric representation of the scene that is imaged. Afterwards, dense reconstruction algorithms are applied to yield a three-dimensional surface model. After georeferencing this model, it can be used to create any kind of orthophoto out of the initial aerial views. To prove the benefits of this approach in comparison to the most common ways of georeferencing aerial imagery, several archaeological case studies are presented. Not only will they showcase the easy workflow and accuracy of the results, but they will also prove that this approach moves beyond current restrictions due to its applicability to datasets that were previously thought to be unsuited for convenient georeferencing.     

基于旅游数字足迹的西安旅游流网络结构研究

Web2.0时代,游客通过互联网获取信息、购买产品,而且还会分享游记、照片。这些游客留在网络上的游记、照片和其它痕迹都含有时空信息,称为"数字足迹"。本文以西安为例,利用游记和照片获取旅游数字足迹,采用数据挖掘方式提取时空信息,并结合社会网络分析法,试图总结西安国内散客旅游流时间及网络结构特征。结果表明,数字足迹研究的时间规律和其它调研结论基本一致;旅游节点间分布不均衡;旅游网络密度低、结构分层明显。本文基于旅游数字足迹的研究,具有很强的可推广价值,可为等旅游管理研究提供新思路。     

Exploring subject positions and multiple temporalities through an Iranian migrant mother's family photograph albums

In this article, I draw on a research study of one Iranian migrant mother's generation of selves through her material configuration of her personal photograph albums and through our verbal reading of her photographs. The research engages in a visual-material feminist ethnographic approach, and is informed by the work of Gillian Rose and the understanding that family photographs are a means by which women negotiate subject positions. In this article, I discuss an unexpected finding of my research, the significance of multiple temporalities in a migrant mother's production of selves. The photo album practices of the participant mother of this study, ‘Parvin’, depart from the common social convention of mothers arranging their photograph albums to chart family growth following the model of milestones occurring over linear developmental time. Parvin does not limit herself to linear developmental time, but rather she mixes up photographs in her post-migration family albums to generate multiple temporalities woven together by an enveloping ‘mixed’ time. Drawing on both Julia Kristeva and Homi Bhaba's theories of temporality and the subject, I suggest that Parvin produces subject positions for self and family through a continual interweaving of a multitude of pasts into the present and through a subsuming of milestones within cyclical family time. Further, I suggest that through her generation of multiple temporalities, Parvin produces the subject position of ‘accommodating mother’. Finally, I highlight the potential afforded by considering the temporal and the spatial together in studies of migrant identity.