text: We propose a method for guiding a photographer to rotate her his smartphone camera to obtain an image that overlaps with another image of the same scene. The other image is taken by another photographer from a different viewpoint. Our method is applicable even when the images do not have overlapping fields of view. Straightforward applications of our method include sharing attention to regions of interest for social purposes, or adding missing images to improve structure for motion results. Our solution uses additional images of the scene, which are often available since many people use their smartphone cameras regularly. These images may be available online from other photographers who are present at the scene. Our method avoids 3D scene reconstruction; it relies instead on a new representation that consists of the spatial orders of the scene points on two axes, x and y. This representation allows a sequence of points to be chosen efficiently and projected onto the photographers images, using epipolar point transfer. Overlaying these epipolar lines on the live preview of the camera produces a convenient interface to guide the user. The method was tested on challenging datasets of images and succeeded in guiding a photographer from one view to a non-overlapping destination view.
  @cite_14: 
  @cite_7: We consider the problem of combining ranking results from various sources. In the context of the Web, the main applications include building meta-search engines, combining ranking functions, selecting documents based on multiple criteria, and improving search precision through word associations. We develop a set of techniques for the rank aggregation problem and compare their performance to that of well-known methods. A primary goal of our work is to design rank aggregation techniques that can e ectively combat ," a serious problem in Web searches. Experiments show that our methods are simple, e cient, and e ective.
  @cite_19: Ranked gene lists are highly instable in the sense that similar measures of differential gene expression may yield very different rankings, and that a small change of the data set usually affects the obtained gene list considerably. Stability issues have long been under-considered in the literature, but they have grown to a hot topic in the last few years, perhaps as a consequence of the increasing skepticism on the reproducibility and clinical applicability of molecular research findings. In this article, we review existing approaches for the assessment of stability of ranked gene lists and the related problem of aggregation, give some practical recommendations, and warn against potential misuse of these methods. This overview is illustrated through an application to a recent leukemia data set using the freely available Bioconductor package GeneSelector.
  @cite_27: Condorcet's principle of choosing the majority alternative whenever one exists is violated not only by Borda's rule but also by any scoring method; nevertheless, the essential property of scoring functions -- "consistency" of the outcome under aggregation of subgroups -- is shown to be compatible with Condorcet's principle. Moreover, these two properties, suitably interpreted, together with neutrality and the Pareto property, determine a unique rule known as Kemeny's rule.
  @cite_15: Photo-sequencing is the problem of recovering the temporal order of a set of still images of a dynamic event, taken asynchronously by a set of uncalibrated cameras. Solving this problem is a first, crucial step for analyzing (or visualizing) the dynamic content of the scene captured by a large number of freely moving spectators. We propose a geometric based solution, followed by rank aggregation to the photo-sequencing problem. Our algorithm trades spatial certainty for temporal certainty. Whereas the previous solution proposed by [4] relies on two images taken from the same static camera to eliminate uncertainty in space, we drop the static-camera assumption and replace it with temporal information available from images taken from the same (moving) camera. Our method thus overcomes the limitation of the static-camera assumption, and scales much better with the duration of the event and the spread of cameras in space. We present successful results on challenging real data sets and large scale synthetic data (250 images).
summary: To allow for geometric and spatial reasoning without direct 3D reconstruction, we use the spatial orderings of the scene points, obtained by rank aggregation. Rank aggregation is the problem of finding a full ranking that agrees with multiple (full or partial) rankings, i.e., a consensus of rankings. It was traditionally studied in the context of social choice and voting theory @cite_27 , but was used also for biological sequence alignment @cite_19 and web page ranking @cite_7 . Recently, it was used to temporally order a collection of images of a dynamic scene @cite_14 @cite_15 . The common rank aggregation problem is known to be NP hard @cite_7 . In our method, we use the Markov chain approximation for rank aggregation, which was proven to be quite effective if the power iteration method is used @cite_7 .