Border ownership coding: global structure in local feature maps
نویسندگان
چکیده
منابع مشابه
Coding of border ownership in monkey visual cortex.
Areas V1 and V2 of the visual cortex have traditionally been conceived as stages of local feature representations. We investigated whether neural responses carry information about how local features belong to objects. Single-cell activity was recorded in areas V1, V2, and V4 of awake behaving monkeys. Displays were used in which the same local feature (contrast edge or line) could be presented ...
متن کاملDynamic coding of border-ownership in visual cortex.
Humans are capable of rapidly determining whether regions in a visual scene appear as figures in the foreground or as background, yet how figure-ground segregation occurs in the primate visual system is unknown. Figures in the environment are perceived to own their borders, and recent neurophysiology has demonstrated that certain cells in primate visual area V2 have border-ownership selectivity...
متن کاملLocal Similarities, Global Coding: An Algorithm for Feature Coding and its Applications
Data coding as a building block of several image processing algorithms has been received great attention recently. Indeed, the importance of the locality assumption in coding approaches is studied in numerous works and several methods are proposed based on this concept. We probe this assumption and claim that taking the similarity between a data point and a more global set of anchor points does...
متن کاملBorder-ownership-dependent tilt aftereffect.
Single-cell recordings from macaque visual cortex have shown orientation-selective neurons in area in V2 code for border ownership [J. Neurosci. 20, 6594 (2000)]: Each piece of contrast border is represented by two pools of neurons whose relative firing rate indicates the side of border ownership. Here we show that the human visual cortex uses a similar coding scheme by demonstrating a border-o...
متن کاملBorder ownership assignment in real images.
We explored whether spectral based cues, such as extremal edges, are useful for border ownership classification in real images, and we analyzed how different environments: indoor vs. outdoor affect the prediction. Our algorithmic approach is based on a random forest classifier using spectral and Gestalt-like texture grouping features. The classifier detects in real-time the points in the image,...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Vision
سال: 2010
ISSN: 1534-7362
DOI: 10.1167/2.7.712