Visual Importance-Biased Image Synthesis Animation

Present ray tracing algorithms are computationally intensive, requiring hours of computing time for complex scenes. Our previous work has dealt with the development of an overall approach to the application of visual attention to progressive and adaptive ray-tracing techniques. The approach facilitates large computational savings by modulating the supersampling rates in an image by the visual importance of the region being rendered. This paper extends the approach by incorporating temporal changes into the models and techniques developed, as it is expected that further efficiency savings can be reaped for animated scenes. Applications for this approach include entertainment, visualisation and simulation

The What-And-Where Filter: A Spatial Mapping Neural Network for Object Recognition and Image Understanding

The What-and-Where filter forms part of a neural network architecture for spatial mapping, object recognition, and image understanding. The Where fllter responds to an image figure that has been separated from its background. It generates a spatial map whose cell activations simultaneously represent the position, orientation, ancl size of all tbe figures in a scene (where they are). This spatial map may he used to direct spatially localized attention to these image features. A multiscale array of oriented detectors, followed by competitve and interpolative interactions between position, orientation, and size scales, is used to define the Where filter. This analysis discloses several issues that need to be dealt with by a spatial mapping system that is based upon oriented filters, such as the role of cliff filters with and without normalization, the double peak problem of maximum orientation across size scale, and the different self-similar interpolation properties across orientation than across size scale. Several computationally efficient Where filters are proposed. The Where filter rnay be used for parallel transformation of multiple image figures into invariant representations that are insensitive to the figures' original position, orientation, and size. These invariant figural representations form part of a system devoted to attentive object learning and recognition (what it is). Unlike some alternative models where serial search for a target occurs, a What and Where representation can he used to rapidly search in parallel for a desired target in a scene. Such a representation can also be used to learn multidimensional representations of objects and their spatial relationships for purposes of image understanding. The What-and-Where filter is inspired by neurobiological data showing that a Where processing stream in the cerebral cortex is used for attentive spatial localization and orientation, whereas a What processing stream is used for attentive object learning and recognition.Advanced Research Projects Agency (ONR-N00014-92-J-4015, AFOSR 90-0083); British Petroleum (89-A-1204); National Science Foundation (IRI-90-00530, Graduate Fellowship); Office of Naval Research (N00014-91-J-4100, N00014-95-1-0409, N00014-95-1-0657); Air Force Office of Scientific Research (F49620-92-J-0499, F49620-92-J-0334

Investigating the timecourse of accessing conversational implicatures during incremental sentence interpretation

Many contextual inferences in utterance interpretation are explained as following from the nature of conversation and the assumption that participants are rational. Recent psycholinguistic research has focussed on certain of these ‘Gricean’ inferences and have revealed that comprehenders can access them in online interpretation. However there have been mixed results as to the time-course of access. Some results show that Gricean inferences can be accessed very rapidly, as rapidly as any other contextually specified information (Sedivy, 2003; Grodner, Klein, Carbery, & Tanenhaus, 2010); while other studies looking at the same kind of inference suggest that access to Gricean inferences are delayed relative to other aspects of semantic interpretation (Huang & Snedeker, 2009; in press). While previous timecourse research has focussed on Gricean inferences that support the online assignment of reference to definite expressions, the study reported here examines the timecourse of access to scalar implicatures, which enrich the meaning of an utterance beyond the semantic interpretation. Even if access to Gricean inference in support of reference assignment may be rapid, it is still unknown whether genuinely enriching scalar implicatures are delayed. Our results indicate that scalar implicatures are accessed as rapidly as other contextual inferences. The implications of our results are discussed in reference to the architecture of language comprehension

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