Predicting Performance in Natural Scene Searches

Completely natural scene search is a paradigm that cannot be directly compared to the typical types of search task studied, where objects are distinct and definable. Here we have look at the possibility of predicting the performance of humans for completely natural scene tasks, using a direct comparison of human performance against new and existing computer models of viewing natural images. For the human task, participants were asked to perform a target present/target absent search task on 120 natural Scenes, the target being a subsection of the Scene and the false-target matched to the scene. The identical task was given to a selection of reproductions of existing computer processing techniques, including Feature congestion (Rosenholtz et al., 2005 SIGCHI 761–770), Saliency (Itti & Koch, 2001 Journal of Electronic Imaging 10 161–169), Target Acquisition Model (Zelinsky, 2008 Psychological Review 115 787–835) and a new variation on the Visual Difference Predictor (To et al., 2008 Proceedings of the Royal Society B: Biological Sciences 275 2299–2308). We show that the models are very bad at generating parameters that predict performance, but that A' of Human performance is predicted pretty well by the simple clutter in the image and these results lead us to conclude that in natural search tasks, the nature of both the Scene and the Target are important, and that the global influence of local feature groups can have an influence of the task difficulty

Search for gross illumination discrepancies in images of natural objects

Shadows may be "discounted" in human visual perception because they do not provide stable, lighting-invariant, information about the properties of objects in the environment. Using visual search, R. A

Quantifying peripheral and foveal perceived differences in natural image patches to predict visual search performance.

Duncan and Humphreys (1989) identified two key factors that affected performance in a visual search task for a target among distractors. The first was the similarity of the target to distractors (TD), and the second was the similarity of distractors to each other (DD). Here we investigate if it is the perceived similarity in foveal or peripheral vision that determines performance. We studied search using stimuli made from patches cut from colored images of natural objects; differences between targets and their modified distractors were estimated using a ratings task peripherally and foveally. We used search conditions in which the targets and distractors were easy to distinguish both foveally and peripherally ("high" stimuli), in which they were difficult to distinguish both foveally and peripherally ("low"), and in which they were easy to distinguish foveally but difficult to distinguish peripherally ("metamers"). In the critical metameric condition, search slopes (change of search time with number of distractors) were similar to the "low" condition, indicating a key role for peripheral information in visual search as both conditions have low perceived similarity peripherally. Furthermore, in all conditions, search slope was well described quantitatively from peripheral TD and DD but not foveal. However, some features of search, such as error rates, do indicate roles for foveal vision too.AEH was supported by a studentship from the BBSRC/UK (BB/F016581/1) and a CASE award from Dstl. RVS received an award from the G. C. Grindley Fund at the University of Cambridge.This is the final version of the article. It first appeared from The Association for Research in Vision and Opthalmology via https://doi.org/10.1167/16.10.1

I Fondamenti della fertilità del terreno

La fertilità del suolo è riconosciuta come valore fondante sin dai pionieri dell'agricoltura biologica ma, ancor oggi, alla conservazione di un suolo fertile non viene attribuita abbastanza attenzione. Eppure l'agricoltura biologica dipende da una buona e naturale fertilità del suolo