Search results for "Object Recognition"

Impairments in top down attentional processes in right parietal patients: Paradoxical functional facilitation in visual search

2014

AbstractIt is well known that the right posterior parietal cortex (PPC) is involved in attentional processes, including binding features. It remains unclear whether PPC is implicated in top-down and/or bottom-up components of attention. We aim to clarify this by comparing performance of seven PPC patients and healthy controls (HC) in a visual search task involving a conflict between top-down and bottom-up processes. This task requires essentially a bottom-up feature search. However, top-down attention triggers feature binding for object recognition, designed to be irrelevant but interfering to the task. This results in top-down interference, prolonging the search reaction time. This interfe…

Did you see that? Dissociating advanced visual information and ball flight constrains perception and action processes during one-handed catching

2013

The integration of separate, yet complimentary, cortical pathways appears to play a role in visual perception and action when intercepting objects. The ventral system is responsible for object recognition and identification, while the dorsal system facilitates continuous regulation of action. This dual-system model implies that empirically manipulating different visual information sources during performance of an interceptive action might lead to the emergence of distinct gaze and movement pattern profiles. To test this idea, we recorded hand kinematics and eye movements of participants as they attempted to catch balls projected from a novel apparatus that synchronised or de-synchronised ac…

Hybrid architecture for shape reconstruction and object recognition

1998

The proposed architecture is aimed to recover 3-D- shape information from gray-level images of a scene; to build a geometric representation of the scene in terms of geometric primitives; and to reason about the scene. The novelty of the architecture is in fact the integration of different approaches: symbolic reasoning techniques typical of knowledge representation in artificial intelligence, algorithmic capabilities typical of artificial vision schemes, and analogue techniques typical of artificial neural networks. Experimental results obtained by means of an implemented version of the proposed architecture acting on real scene images are reported to illustrate the system capabilities.

2017

In continuous flash suppression (CFS), a dynamic noise masker, presented to one eye, suppresses conscious perception of a test stimulus, presented to the other eye, until the suppressed stimulus comes to awareness after few seconds. But what do we see breaking the dominance of the masker in the transition period? We addressed this question with a dual-task in which observers indicated (i) whether the test object was left or right of the fixation mark (localization) and (ii) whether it was a face or a house (categorization). As done recently (Stein et al., 2011), we used two experimental varieties to rule out confounds with decisional strategy. In the terminated mode, stimulus and masker wer…

Recognition of polychromatic three-dimensional objects

2004

We propose to use optical multichannel correlation in various chromatic systems to obtain a setup for recognition of polychromatic three-dimensional (3-D) objects based on Fourier-transform profilometry. Because red-green-blue color components are not able to split the luminance information of objects in a defined component, when the 3-D objects are brighter than the reference objects the correlation result gives false alarms. We demonstrate that it is possible to use different color spaces that can split luminance from chromatic information to yield adequate recognition of polychromatic 3-D objects. We show experimental results that prove the utility of the proposed method.

Hybrid Methods for Robust Irradiance Analysis and 3-D Shape Reconstruction from Images

1994

The analysis of the differential structure of images is an interesting task in machine vision, among other reasons because it can provide relevant featural representation of images, suited for higher level information processing task like geometry reconstruction and object recognition. The importance of invariants of the field of isophotae on lambertian surfaces in shape perception by means of chiaroscuro is discussed in (Koenderink and Van Doom, 1980). In their approach to shape from shading, (Breton et al, 1992) represent the shading of the image by means of its shading flow field, i.e. by the first order differential structure of the image expressed as the isoluminance direction and grad…

Rethinking the sGLOH Descriptor

2018

sGLOH (shifting GLOH) is a histogram-based keypoint descriptor that can be associated to multiple quantized rotations of the keypoint patch without any recomputation. This property can be exploited to define the best distance between two descriptor vectors, thus avoiding computing the dominant orientation. In addition, sGLOH can reject incongruous correspondences by adding a global constraint on the rotations either as an a priori knowledge or based on the data. This paper thoroughly reconsiders sGLOH and improves it in terms of robustness, speed and descriptor dimension. The revised sGLOH embeds more quantized rotations, thus yielding more correct matches. A novel fast matching scheme is a…

A neural network based automatic road signs recognizer

2003

Automatic road sign recognition systems are aimed at detection and recognition of one or more road signs from real-world color images. In this research, road signs are detected and extracted from real world scenes on the basis of their color and shape features. A dynamic region growing technique is adopted to enhance color segmentation results obtained in the HSV color space. The technique is based on a dynamic threshold that reduces the effect of hue instability in real scenes due to external brightness variation. Classification is then performed on extracted candidate regions using multilayer perceptron neural networks. The obtained results show good detection and recognition rates of the…

Kernel manifold alignment for domain adaptation

2016

The wealth of sensory data coming from different modalities has opened numerous opportu- nities for data analysis. The data are of increasing volume, complexity and dimensionality, thus calling for new methodological innovations towards multimodal data processing. How- ever, multimodal architectures must rely on models able to adapt to changes in the data dis- tribution. Differences in the density functions can be due to changes in acquisition conditions (pose, illumination), sensors characteristics (number of channels, resolution) or different views (e.g. street level vs. aerial views of a same building). We call these different acquisition modes domains, and refer to the adaptation proble…

A modeling study suggesting how a reduction in the context-dependent input on CA1 pyramidal neurons could generate schizophrenic behavior.

2011

The neural mechanisms underlying schizophrenic behavior are unknown and very difficult to investigate experimentally, although a few experimental and modeling studies suggested possible causes for some of the typical psychotic symptoms related to this disease. The brain region most involved in these processes seems to be the hippocampus, because of its critical role in establishing memories for objects or events in the context in which they occur. In particular, a hypofunction of the N-methyl-D-aspartate (NMDA) component of the synaptic input on the distal dendrites of CA1 pyramidal neurons has been suggested to play an important role for the emergence of schizophrenic behavior. Modeling st…