Results 31 to 40 of about 1,525,474 (355)
Polyhedral object recognition by indexing [PDF]
Pattern Recognition, 1995 In computer vision, the indexing problem is the problem of recognizing a few objects in a large database of objects while avoiding the help of the classical image-feature-to-object-feature matching paradigm. In this paper we address the problem of recognizing 3-D polyhedral objects from 2-D images by indexing.
Horaud, Radu, Sossa, Humberto
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Sparse distributed localized gradient fused features of objects [PDF]
Pattern Recognition, Available online 31 October 2014, 2014 The sparse, hierarchical, and modular processing of natural signals is related to the ability of humans to recognize objects with high accuracy. In this study, we report a sparse feature processing and encoding method, which improved the recognition performance of an automated object recognition system.
arxiv +1 more source
Text-driven object affordance for guiding grasp-type recognition in multimodal robot teaching [PDF]
, 2021 This study investigates how text-driven object affordance, which provides prior knowledge about grasp types for each object, affects image-based grasp-type recognition in robot teaching. The researchers created labeled datasets of first-person hand images to examine the impact of object affordance on recognition performance.
arxiv +1 more source
Cross-modal object recognition is viewpoint-independent. [PDF]
PLoS ONE, 2007 Previous research suggests that visual and haptic object recognition are viewpoint-dependent both within- and cross-modally. However, this conclusion may not be generally valid as it was reached using objects oriented along their extended y-axis ...
Simon Lacey, Andrew Peters, K Sathian
doaj +1 more source
Probabilistic Search for Object Segmentation and Recognition [PDF]
, 2002 The problem of searching for a model-based scene interpretation is analyzed within a probabilistic framework. Object models are formulated as generative models for range data of the scene. A new statistical criterion, the truncated object probability, is
Hillenbrand, Dr. Ulrich +1 more
core +5 more sources
Frontiers in Behavioral Neuroscience, 2022 Object recognition, the ability to discriminate between a novel and a familiar stimulus, is critically dependent upon the perirhinal cortex. Neural response reductions upon repetition of a stimulus, have been hypothesized to be the mechanism within ...
Alexandra R. Outram +3 more
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Cognitive Aspects of Object Recognition – Recognition of Objects by Texture [PDF]
Procedia Computer Science, 2015 AbstractTo study human image cognition is more than ever an important topic since the number of vision-based materials has been increased over the years. Texture seems to be a powerful tool to describe the appearances of objects. Therefore, very flexible and powerful texture descriptors are of importance that allow to recognize the texture and to ...
openaire +1 more source
Object Recognition: Complexity of Recognition Strategies [PDF]
Current Biology, 2018 Primate brains and state-of-the-art convolutional neural networks can recognize many faces, objects and scenes, though how they do so is often mysterious. New research unveils some of the mystery, revealing unexpected complexity in the recognition strategies of rodents.
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Object Recognition and Dorsal Stream Vulnerabilities in Children With Early Brain Damage
Frontiers in Human Neuroscience, 2022 AimVisual functions of the dorsal stream are considered vulnerable in children with early brain damage. Considering the recognition of objects in suboptimal representations a dorsal stream dysfunction, we examined whether children with early brain damage
Ymie J. van der Zee +3 more
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Frontiers in Behavioral Neuroscience, 2022 Infusing the amnesic agent zeta inhibitory peptide (ZIP) into the dorsal hippocampus disrupts established long-term object location recognition memory without affecting object identity recognition, which likely depends on the perirhinal cortex.
Keanan Augereau +2 more
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