首页> 外文会议>1996 International Conference on Artificial Neural Networks - ICANN 96 Bochum, Germany, July 16-19, 1996 >Visual Recognition Based on Coding in Temporal Cortex: Analysis of Pattern Configuration and Generalisation across Viewing Conditions without Mental Rotation
【24h】

Visual Recognition Based on Coding in Temporal Cortex: Analysis of Pattern Configuration and Generalisation across Viewing Conditions without Mental Rotation

机译:基于时间皮层编码的视觉识别:无视旋转情况下跨视域的模式配置和泛化分析

获取原文
获取原文并翻译 | 示例

摘要

A model of recognition is described that is based on cell properties in the ventral cortical stream of visual processing in the primate brain. At a critical intermediate stage in this system Elaborate feature sensitive cells respond selectively to visual features in a way that depends on size (+- octave), orientation (+-45) but does not depend on position within central vision (+-5). These features are simple conjunctions of 2-D elements (e.g. a horizontal dark area above a dark smoothly convex area). Such features can arise either as elements of an objects surface pattern or as 3-D component parts of the object. By requiring a combination of several such features without regard to their position within the central region of the visual image, Pattern sensitive cells at higher levels can become selective for complex configurations that typify objects experienced in particular viewing conditions. Given that input features are specified in approximate size and orientation, initial cellular 'representations' of the visual appearance of object type (or object example) are also selective orientation and size. Such represnetations are sensitive to object view (+-40-60) because visual features disappear as objects are rotated in perspective. Combined sensitivity to multiple 2-D features independent of their position establishes selectivity for configuration of object parts (from one view) because rearranged configurations yield images lacking some of features present in the normal configuration. Different neural populations appear to be tuned to particular components of the same biological object (e.g. face, eyes, hands, legs), perhaps because the independent articulation of these components gives rise to correlated activity in different sets of input visual features. Generalisation over viewing conditions for a given object can be established by hierarchically pooling outputs of view specific cells. Such pooling could depend on the continuity in experience across viewing conditions: different object parts are seen together and different views are seen in succession when the observer walks around the object. For any familiar object, more cells will be tuned to the configuration of the objects features present in the view(s) frequently experienced. Therefore, activity amongst the population of cells selective for the objects appearance will accumulate more slowly when the object is seen in an unusual orientation or view. this accounts for increased time to recognise rotated views without the need to postulate mental rotation or transformations of novel views to align with neural representations of familiar iews. The model is in accordance with known physiological findings and matches the behavioural performance of the mammalian visual system which displays view, orientation and size selectivity when learning about new pattern configurations.
机译:描述了一种识别模型,该模型基于灵长类动物大脑视觉处理的腹侧皮质视觉流中的细胞特性。在此系统的关键中间阶段,精细的特征敏感单元以不依赖于大小(+-八度),方向(+ -45)但不依赖于中心视力内的位置(+ -5)的方式选择性地对视觉特征作出响应。这些功能是2D元素的简单结合(例如,在深色平滑凸出区域上方的水平深色区域)。这样的特征既可以作为物体表面图案的元素出现,也可以作为物体的3-D组成部分出现。通过要求几个这样的特征的组合而不考虑它们在视觉图像中心区域内的位置,图案敏感单元在较高级别上可以对代表特定观看条件下经历的物体的复杂配置具有选择性。假定输入特征以近似的大小和方向指定,则对象类型(或对象示例)的视觉外观的初始单元格“表示”也是选择性的方向和大小。这种重新呈现对对象视图(+ -40-60)敏感,因为随着对象在透视图中旋转,视觉特征会消失。对多个2-D特征的敏感性独立于它们的位置,从而为对象部件的构造(从一个视图)建立了选择性,因为重新排列的构造会产生缺少正常构造中某些特征的图像。不同的神经种群似乎已针对同一生物对象的特定组件(例如脸,眼,手,腿)进行了调整,这可能是因为这些组件的独立表达会导致在不同的输入视觉特征集中产生相关的活动。可以通过分层汇总特定于视图的单元格的输出来建立针对给定对象的查看条件的一般化。这种合并可能取决于跨观看条件的体验的连续性:当观察者在对象周围行走时,可以同时看到不同的对象部分,并且可以连续看到不同的视图。对于任何熟悉的对象,更多的单元将被调整为经常遇到的视图中存在的对象特征的配置。因此,当以不同寻常的方向或视角看物体时,对物体外观具有选择性的细胞群中的活动将更加缓慢地积累。这就需要花费更多的时间来识别旋转的视图,而无需假设心理旋转或将新颖的视图转换为与熟悉的同工的神经表示保持一致。该模型符合已知的生理学发现,并且与哺乳动物视觉系统的行为表现相匹配,该哺乳动物视觉系统在学习新的模式配置时会显示视图,方向和尺寸选择性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号