Bridging the Gap Between Object-Based Attention and Texton-Based Segmentation: How Attention Spreads Through Orientation-Defined Textures
نویسندگان
چکیده
Many recent studies of object-based attention (OBA) have suggested that the underlying units of attention are often discrete objects, through which attention readily spreads. However, the relationship of such experiments to the basic visual features (‘textons’) which guide the segmentation of visual scenes into ‘objects’ remains largely unexplored. Here we bridge this gap for one of the most conspicuous features of early vision: orientation. We do so in a study of how attention spreads through simple static orientation-defined textures (ODTs), and across texture-defined boundaries. Much work in the segmentation literature suggests that orientation-based texture segmentation (OBTS) is guided by orientation gradients, and our previous work suggests that it is also influenced by ODT curvatures. We suggest here that attention should respect ODT boundaries defined by both orientation and curvature differences, and we also predict that the flow of attention should not depend on the general direction (i.e. the ‘grain’) of the texture — in contradiction to previous findings in the OBA literature. We explore such predictions using both spatial-cueing and dividedattention paradigms on various ODTs, both uniform (one ‘object’) and discontinuous (two ‘objects’). Contrary to previous studies, we find that the texture’s ‘main direction’ has no effect: attention flows just as readily with vs. against the ‘grain’ of ODTs. At the same time, texture-defined discontinuities have a major effect: attention flows less readily across texture boundaries which are defined by either orientation or curvature. These effects replicated across multiple paradigms and dependent measures, and also held for jittered ODTs, wherein the effects must be due to global structure as opposed to local good continuation. We conclude that uniform ODTs are single objects from an attentional point of view, while discontinuous ODTs — with the discontinuities defined in either orientation or curvature — are processed as multiple objects. Collectively these experiments begin to reveal how the ‘objects’ of OBA are formed from simpler visual features.
منابع مشابه
Attention, segregation, and textons: Bridging the gap between object-based attention and texton-based segregation
Studies of object-based attention (OBA) have suggested that attentional selection is intimately associated with discrete objects. However, the relationship of this association to the basic visual features ('textons') which guide the segregation of visual scenes into 'objects' remains largely unexplored. Here we study this hypothesized relationship for one of the most conspicuous features of ear...
متن کاملTexture segregation by visual cortex: Perceptual grouping, attention, and learning
A neural model called dARTEX is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model unifies five interacting processes: region-based texture classification, contour-based boundary grouping, surface filling-in, spatial attention, and object attention. The model shows how form boundaries can determine regions in which sur...
متن کاملTexture segregation by visual cortex:
A neural model called dARTEX is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model unifies five interacting processes: regionbased texture classification, contour-based boundary grouping, surface filling-in, spatial attention, and object attention. The model shows how form boundaries can determine regions in which surf...
متن کاملWavelet Based Histogram Method for Classification of Textures
To achieve high accuracy in classification the present paper proposes a new method on texton pattern detection based on wavelets. Each texture analysis method depends upon how the selected texture features characterizes image. Whenever a new texture feature is derived it is tested whether it precisely classifies the textures. Here not only the texture features are important but also the way in ...
متن کاملSemantic segmentation of images exploiting DCT based features and random forest
This paper presents an approach for generating class-specific image segmentation. We introduce two novel features that use the quantized data of the Discrete Cosine Transform (DCT) in a Semantic Texton Forest based framework (STF), by combining together colour and texture information for semantic segmentation purpose. The combination of multiple features in a segmentation system is not a straig...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003