scispace - formally typeset
Topic

Feature detection (computer vision)

About: Feature detection (computer vision) is a(n) research topic. Over the lifetime, 25605 publication(s) have been published within this topic receiving 516757 citation(s).

...read more

Papers
More filters

Journal ArticleDOI
Abstract: Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components. A second constraint is needed. A method for finding the optical flow pattern is presented which assumes that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image. An iterative implementation is shown which successfully computes the optical flow for a number of synthetic image sequences. The algorithm is robust in that it can handle image sequences that are quantized rather coarsely in space and time. It is also insensitive to quantization of brightness levels and additive noise. Examples are included where the assumption of smoothness is violated at singular points or along lines in the image.

...read more

10,249 citations


Proceedings ArticleDOI
17 Jun 2006-
TL;DR: This paper presents a method for recognizing scene categories based on approximate global geometric correspondence that exceeds the state of the art on the Caltech-101 database and achieves high accuracy on a large database of fifteen natural scene categories.

...read more

Abstract: This paper presents a method for recognizing scene categories based on approximate global geometric correspondence. This technique works by partitioning the image into increasingly fine sub-regions and computing histograms of local features found inside each sub-region. The resulting "spatial pyramid" is a simple and computationally efficient extension of an orderless bag-of-features image representation, and it shows significantly improved performance on challenging scene categorization tasks. Specifically, our proposed method exceeds the state of the art on the Caltech-101 database and achieves high accuracy on a large database of fifteen natural scene categories. The spatial pyramid framework also offers insights into the success of several recently proposed image descriptions, including Torralba’s "gist" and Lowe’s SIFT descriptors.

...read more

8,415 citations


10


Journal ArticleDOI
Barbara Zitová1, Jan Flusser1Institutions (1)
TL;DR: A review of recent as well as classic image registration methods to provide a comprehensive reference source for the researchers involved in image registration, regardless of particular application areas.

...read more

Abstract: This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration geometrically align two images (the reference and sensed images). The reviewed approaches are classified according to their nature (areabased and feature-based) and according to four basic steps of image registration procedure: feature detection, feature matching, mapping function design, and image transformation and resampling. Main contributions, advantages, and drawbacks of the methods are mentioned in the paper. Problematic issues of image registration and outlook for the future research are discussed too. The major goal of the paper is to provide a comprehensive reference source for the researchers involved in image registration, regardless of particular application areas. q 2003 Elsevier B.V. All rights reserved.

...read more

6,465 citations


6


Book
01 Dec 2003-
TL;DR: 1. Fundamentals of Image Processing, 2. Intensity Transformations and Spatial Filtering, and 3. Frequency Domain Processing.

...read more

Abstract: 1. Introduction. 2. Fundamentals. 3. Intensity Transformations and Spatial Filtering. 4. Frequency Domain Processing. 5. Image Restoration. 6. Color Image Processing. 7. Wavelets. 8. Image Compression. 9. Morphological Image Processing. 10. Image Segmentation. 11. Representation and Description. 12. Object Recognition.

...read more

6,204 citations


Book
01 Jan 1993-
TL;DR: The digitized image and its properties are studied, including shape representation and description, and linear discrete image transforms, and texture analysis.

...read more

Abstract: List of Algorithms. Preface. Possible Course Outlines. 1. Introduction. 2. The Image, Its Representations and Properties. 3. The Image, Its Mathematical and Physical Background. 4. Data Structures for Image Analysis. 5. Image Pre-Processing. 6. Segmentation I. 7. Segmentation II. 8. Shape Representation and Description. 9. Object Recognition. 10. Image Understanding. 11. 3d Geometry, Correspondence, 3d from Intensities. 12. Reconstruction from 3d. 13. Mathematical Morphology. 14. Image Data Compression. 15. Texture. 16. Motion Analysis. Index.

...read more

5,344 citations


Network Information
Related Topics (5)
Feature extraction

111.8K papers, 2.1M citations

94% related
Image segmentation

79.6K papers, 1.8M citations

94% related
Edge detection

25.5K papers, 486.4K citations

93% related
Image texture

29.1K papers, 736.4K citations

93% related
Binary image

26.2K papers, 405.2K citations

93% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20222
2021143
2020186
2019221
2018242
2017678

Top Attributes

Show by:

Topic's top 5 most impactful authors

Azriel Rosenfeld

24 papers, 657 citations

Qi Tian

22 papers, 1.5K citations

Tomoharu Nagao

15 papers, 173 citations

Sonya Coleman

12 papers, 44 citations

Peter Corcoran

10 papers, 860 citations