Browsing CSAIL Technical Reports (July 1, 2003 - present) by Subject "object recognition"
Now showing items 1-18 of 18
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A new biologically motivated framework for robust object recognition
(2004-11-14)In this paper, we introduce a novel set of features for robust object recognition, which exhibits outstanding performances on a variety ofobject categories while being capable of learning from only a fewtraining examples. ... -
A Theory of Object Recognition: Computations and Circuits in the Feedforward Path of the Ventral Stream in Primate Visual Cortex
(2005-12-19)We describe a quantitative theory to account for the computations performed by the feedforward path of the ventral stream of visual cortex and the local circuits implementing them. We show that a model instantiating the ... -
Boosting a Biologically Inspired Local Descriptor for Geometry-free Face and Full Multi-view 3D Object Recognition
(2005-07-07)Object recognition systems relying on local descriptors are increasingly used because of their perceived robustness with respect to occlusions and to global geometrical deformations. Descriptors of this type -- based on ... -
Comparing Visual Features for Morphing Based Recognition
(2005-05-25)This thesis presents a method of object classification using the idea of deformable shape matching. Three types of visual features, geometric blur, C1 and SIFT, are used to generate feature descriptors. These feature ... -
Component based recognition of objects in an office environment
(2003-11-28)We present a component-based approach for recognizing objectsunder large pose changes. From a set of training images of a givenobject we extract a large number of components which are clusteredbased on the similarity of ... -
Efficient Image Matching with Distributions of Local Invariant Features
(2004-11-22)Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature sets' similarity via a voting scheme (which ... -
Examining high level neural representations of cluttered scenes
(2010-07-29)Humans and other primates can rapidly categorize objects even when they are embedded in complex visual scenes (Thorpe et al., 1996; Fabre-Thorpe et al., 1998). Studies by Serre et al., 2007 have shown that the ability of ... -
Face processing in humans is compatible with a simple shape-based model of vision
(2004-03-05)Understanding how the human visual system recognizes objects is one of the key challenges in neuroscience. Inspired by a large body of physiological evidence (Felleman and Van Essen, 1991; Hubel and Wiesel, 1962; Livingstone ... -
Faces as a "Model Category" for Visual Object Recognition
(2013-03-18)Visual recognition is an important ability that is central to many everyday tasks such as reading, navigation and social interaction, and is therefore actively studied in neuroscience, cognitive psychology and artificial ... -
From primal templates to invariant recognition
(2010-12-04)We can immediately recognize novel objects seen only once before -- in different positions on the retina and at different scales (distances). Is this ability hardwired by our genes or learned during development -- and ... -
Learning Generic Invariances in Object Recognition: Translation and Scale
(2010-12-30)Invariance to various transformations is key to object recognition but existing definitions of invariance are somewhat confusing while discussions of invariance are often confused. In this report, we provide an operational ... -
On the difficulty of feature-based attentional modulations in visual object recognition: A modeling study.
(2004-01-14)Numerous psychophysical experiments have shown an important role for attentional modulations in vision. Behaviorally, allocation of attention can improve performance in object detection and recognition tasks. At the neural ... -
Pyramid Match Kernels: Discriminative Classification with Sets of Image Features
(2005-03-17)Discriminative learning is challenging when examples are setsof local image features, and the sets vary in cardinality and lackany sort of meaningful ordering. Kernel-based classificationmethods can learn complex decision ... -
Realistic Modeling of Simple and Complex Cell Tuning in the HMAXModel, and Implications for Invariant Object Recognition in Cortex
(2004-07-27)Riesenhuber \& Poggio recently proposed a model of object recognitionin cortex which, beyond integrating general beliefs about the visualsystem in a quantitative framework, made testable predictions aboutvisual processing. ... -
Receptive field structures for recognition
(2005-03-01)Localized operators, like Gabor wavelets and difference-of-Gaussian filters, are considered to be useful tools for image representation. This is due to their ability to form a Âsparse code that can serve as a basis set ... -
Rotation Invariant Object Recognition from One Training Example
(2004-04-27)Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. Such a descriptor--based on a set of ... -
Selectivity of Local Field Potentials in Macaque Inferior Temporal Cortex
(2004-09-21)While single neurons in inferior temporal (IT) cortex show differential responses to distinct complex stimuli, little is known about the responses of populations of neurons in IT. We recorded single electrode data, including ... -
Ultra-fast Object Recognition from Few Spikes
(2005-07-06)Understanding the complex brain computations leading to object recognition requires quantitatively characterizing the information represented in inferior temporal cortex (IT), the highest stage of the primate visual stream. ...