Rapid Visual Categorization is not Guided by Early Salience-Based Selection

The current dominant visual processing paradigm in both human and machine research is the feedforward, layered hierarchy of neural-like processing elements. Within this paradigm, visual saliency is seen by many to have a specific role, namely that of early selection. Early selection is thought to enable very fast visual performance by limiting processing to only the most salient candidate portions of an image. This strategy has led to a plethora of saliency algorithms that have indeed improved processing time efficiency in machine algorithms, which in turn have strengthened the suggestion that human vision also employs a similar early selection strategy. However, at least one set of critical tests of this idea has never been performed with respect to the role of early selection in human vision. How would the best of the current saliency models perform on the stimuli used by experimentalists who first provided evidence for this visual processing paradigm? Would the algorithms really provide correct candidate sub-images to enable fast categorization on those same images? Do humans really need this early selection for their impressive performance? Here, we report on a new series of tests of these questions whose results suggest that it is quite unlikely that such an early selection process has any role in human rapid visual categorization.Comment: 22 pages, 9 figure

An Enhancement Method for Japanese-English Automated Translation

We present a method for improving existing statistical machine translation methods using a knowledge base compiled from a bilingual corpus as well as sequence alignment and pattern matching techniques from the area of machine learning and bioinformatics. An alignment algorithm identifies similar sentences, which are then used to construct a better word order for the translation. Our preliminary test results indicate a significant improvement of the translation quality.

Rheologische Untersuchungen an nativen Biofilmen von Pseudomonas aeruginosa

Biofilme sind die universelle Lebensform von Mikroorganismen. Erst gegen Ende des 20. Jahrhunderts wurde intensiver mit ihrer Untersuchung begonnen. Über viele grundlegende Mechanismen herrscht auch heute noch Ungewissheit. Als Biofilme bezeichnet man unterschiedliche mikrobielle Aggregate. Gemeinsames Kennzeichen ist das Einbetten der Organismen in eine dreidimensionale Matrix aus extrazellulären polymeren Substanzen (EPS). Diese Matrix hält die Mikroorganismen zusammen, und ermöglicht ggf. eine Bindung an den Oberflächen. Biofilme können sich an diversen Grenzflächen zwischen festen, flüssigen und gasförmigen Medien bilden und so an Geräten, in Rohrleitungen oder an Oberflächen auch enormen wirtschaftlichen Schaden anrichten. In der rheologischen Studie wurden Biofilme des Bakteriums Pseudomonas aeruginosa untersucht, und mechanische Eigenschaften der EPS Matrixstruktur charakterisiert. Neben transienten Fließeigenschaften wurden auch die Einflüsse von positiv geladenen Ionen wie Kalzium, Magnesium und Mangan auf die Netzwerkstabilität gemessen. Die Biofilme zeigten viskoelastisches Verhalten mit Netzwerkpunkten, die durch Verschlaufungen verursacht wurden. Bei Frequenztests wurden Plateaubereiche mit Gleichgewichtsschermodulwerten zwischen 17 und 210 Pa bei 24h alten Biofilmen, in Abhängigkeit von der molekularen Struktur der EPS beobachtet. Der Einfluss von Ionen führte in Abhängigkeit der Konzentration zu fest vernetzten Systemen ohne Relaxation. Der Einfluss von Strukturmerkmalen des Alginates auf die mechanische Stabilität der EPS Matrix wurde beispielhaft an den Stämmen FRD1 und FRD1153 untersucht. Die Abwesenheit von Acetylgruppen in den Alginatketten von P. aeruginosa FRD1153 zeigte sich in schwächeren Netzwerkstrukturen und kleineren Plateauwerten im Vergleich zu FRD1. Relaxationsprozesse führten zu einer mittleren Lebensdauer der Verbindungspunkte zwischen 110 ms und 17 s. Die Zugabe von mehrwertigen Gegenionen induzierte stabile Verbindungspunkte über Coulombsche Kräfte, die allerdings unterschiedlich stabil waren. Die Resultate können für Modelle genutzt werden, die Biofilme in natürlicher Umgebung beschreiben, oder alternativ Informationen zur Entwicklung neuer Medikamente oder Reiniger liefern, sobald die Mikromechanismen der Biofilmbildung und Stabilität geklärt sind

A Focus on Selection for Fixation

A computational explanation of how visual attention, interpretation of visual stimuli, and eye movements combine to produce visual behavior, seems elusive. Here, we focus on one component: how selection is accomplished for the next fixation. The popularity of saliency map models drives the inference that this is solved, but we argue otherwise. We provide arguments that a cluster of complementary, conspicuity representations drive selection, modulated by task goals and history, leading to a hybrid process that encompasses early and late attentional selection. This design is also constrained by the architectural characteristics of the visual processing pathways. These elements combine into a new strategy for computing fixation targets and a first simulation of its performance is presented. A sample video of this performance can be found by clicking on the "Supplementary Files" link under the "Article Tools" heading

Focusing on Selection for Fixation

Building on our presentation at MODVIS 2015, we continue in our quest to discover a functional, computational, explanation of the relationship among visual attention, interpretation of visual stimuli, and eye movements, and how these produce visual behavior. Here, we focus on one component, how selection is accomplished for the next fixation. The popularity of saliency map models drives the inference that this is solved; we suggested otherwise at MODVIS 2015. Here, we provide additional empirical and theoretical arguments. We then develop arguments that a cluster of complementary, conspicuity representations drive selection, modulated by task goals and history, leading to a blended process that encompasses early, mid-level and late attentional selection and reflects the differences between central and peripheral processes. This design is also constrained by the architectural characteristics of the visual processing pathways, specifically, the boundary problem, as well as retinal photoreceptor distribution. These elements combine into a new strategy for computing fixation targets and a first simulation of its performance is presented

SMILER: Consistent and Usable Saliency Model Implementations

The Saliency Model Implementation Library for Experimental Research (SMILER) is a new software package which provides an open, standardized, and extensible framework for maintaining and executing computational saliency models. This work drastically reduces the human effort required to apply saliency algorithms to new tasks and datasets, while also ensuring consistency and procedural correctness for results and conclusions produced by different parties. At its launch SMILER already includes twenty three saliency models (fourteen models based in MATLAB and nine supported through containerization), and the open design of SMILER encourages this number to grow with future contributions from the community. The project may be downloaded and contributed to through its GitHub page:https://github.com/tsotsoslab/smile