Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Visual System01:26

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
Vision01:24

Vision

Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
Encoding01:19

Encoding

Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...
Stereotype Content Model02:16

Stereotype Content Model

The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence categorization, a person will feel...
Schemas01:42

Schemas

A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Interferences in Match Kernels.

IEEE transactions on pattern analysis and machine intelligence·2016
Same author

Label-Embedding for Image Classification.

IEEE transactions on pattern analysis and machine intelligence·2015
Same author

Good practice in large-scale learning for image classification.

IEEE transactions on pattern analysis and machine intelligence·2014
Same author

Asymmetric distances for binary embeddings.

IEEE transactions on pattern analysis and machine intelligence·2013
Same author

Iterative quantization: a Procrustean approach to learning binary codes for large-scale image retrieval.

IEEE transactions on pattern analysis and machine intelligence·2013
Same author

Distance-based image classification: generalizing to new classes at near-zero cost.

IEEE transactions on pattern analysis and machine intelligence·2013

Related Experiment Video

Updated: Jul 4, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

Universal and adapted vocabularies for generic visual categorization.

Florent Perronnin1

  • 1Xerox Research Centre Europe, Meylan, France. Florent.Perronnin@xrce.xerox.com

IEEE Transactions on Pattern Analysis and Machine Intelligence
|June 14, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for generic visual categorization (GVC) using universal and class-specific vocabularies. This approach improves image classification accuracy with efficient computational cost.

More Related Videos

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
07:31

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Related Experiment Videos

Last Updated: Jul 4, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
07:31

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Machine Learning

Background:

  • Generic Visual Categorization (GVC) involves assigning semantic labels to images, a complex task due to variations in objects, scenes, lighting, and occlusion.
  • Current GVC systems often rely on visual vocabularies and histograms of visual word counts for image characterization.

Purpose of the Study:

  • To propose a novel and practical approach for GVC using a universal vocabulary and adaptive class vocabularies.
  • To enhance image representation by employing a set of histograms per class, indicating the best model fit (universal or class-specific).

Main Methods:

  • Developed a GVC framework utilizing a universal vocabulary for all image classes and class-specific vocabularies adapted from the universal one.
  • Applied the framework to local image features, including Scale-Invariant Feature Transform (SIFT) descriptors and high-level co-occurrence histograms.
  • Evaluated the approach on two challenging datasets: an in-house 19-category database and the PASCAL VOC 2006 dataset.

Main Results:

  • The proposed GVC approach achieved state-of-the-art performance on benchmark datasets.
  • Demonstrated effectiveness with both low-level (SIFT) and high-level image features.
  • The method proved computationally efficient, offering practical advantages.

Conclusions:

  • The novel GVC framework with universal and class-specific vocabularies offers a significant advancement in image classification.
  • The approach provides a robust and efficient solution for complex visual categorization tasks.
  • Experimental results validate the method's superior performance and modest computational requirements.