Learning to Link Visual Contours

Learning to Link Visual Contours

In complex visual scenes, linking related contour elements is important for object recognition. This process, thought to be stimulus driven and hard wired, has substrates in primary visual cortex (V1). Here, however, we find contour integration in V1 to depend strongly on perceptual learning and top-down influences that are specific to contour detection. In naive monkeys, the information about ...

Learning to Track the Visual Motion of Contours

A development of a method for tracking visual contours is described. Given an “untrained” tracker, a training motion of an object can be observed over some extended time and stored as an image sequence. The image sequence is used to learn parameters in a stochastic differential equation model. These are used, in turn, to build a tracker whose predictor imitates the motion in the training set. T...

Learning Accurate Active Contours

Focus of research in Active contour models (ACM) area is mainly on development of various energy functions based on physical intuition. In this work, instead of designing a new energy function, we generate a multitude of contour candidates using various values of ACM parameters, assess their quality, and select the most suitable one for an object at hand. A random forest is trained to make cont...

Orientation-selective adaptation to illusory contours in human visual cortex.

Humans can perceive illusory or subjective contours in the absence of any real physical boundaries. We used an adaptation protocol to look for orientation-selective neural responses to illusory contours defined by phase-shifted abutting line gratings in the human visual cortex. We measured functional magnetic resonance imaging (fMRI) responses to illusory-contour test stimuli after adapting to ...

Visual interpolation and extrapolation of contours