Performance assessment of feature detection algorithms: a methodology and case study on corner detectors

Rockett, Peter

doi:10.1109/tip.2003.818041

Cited by 64 publications

(23 citation statements)

References 22 publications

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“…This algorithm is described e.g. in MohannaMohktarian, 2001or Rockett, 2003 A er performing all these operations the corners of the marker are available. For proper marker registration it is now necessary to create a transformation which allows us to project the object given by these corners from the camera perspective to its original shape.…”

Section: Methods and Resourcesmentioning

confidence: 99%

Augmented reality usage for prototyping speed up

Šťastný¹,

Procházka²,

Koubek³

et al. 2014

Acta Univ. Agric. Silvic. Mendelianae Brun.

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AbstractŠŤASTNÝ, J., PROCHÁZKA, D., KOUBEK, T., LANDA, J.: Augmented reality usage for prototyping speed up. Acta univ. agric. et silvic. Mendel. Brun., 2011, LIX, No. 2, pp. 353-360 The integral part of production process in many companies is prototyping. Although, these companies commonly have high quality visualization tools (large screen projections, virtual reality), prototyping was never abandoned. There is a number of reasons. The most important is the possibility of model observation from any angle without any physical constraints and its haptic feedback. The interactivity of model adjustments is important as well. The direct work with the model allows the designers to focus on the creative process more than work with a computer. There is still a problem with a diffi cult adjustability of the model. More signifi cant changes demand completely new prototype or at least longer time for its realization. The fi rst part of the article describes our approach for solution of this problem by means of Augmented Reality. The merging of the real world model and digital objects allows streamline the work with the model and speed up the whole production phase signifi cantly. The main advantage of augmented reality is the possibility of direct manipulation with the scene using a portable digital camera. Also adding digital objects into the scene could be done using identifi cation markers placed on the surface of the model. Therefore it is not necessary to work with special input devices and lose the contact with the real world model. Adjustments are done directly on the model. The key problem of outlined solution is the ability of identifi cation of an object within the camera picture and its replacement with the digital object. The second part of the article is focused especially on the identifi cation of exact position and orientation of the marker within the picture. The identifi cation marker is generalized into the triple of points which represents a general plane in space. There is discussed the space identifi cation of these points and the description of representation of their position and orientation be means of transformation matrix. This matrix is used for rendering of the graphical objects (e. g. in OpenGL and Direct3D).augmented reality, prototyping, pose estimation, transformation matrix European manufacturers face strong competitive pressure which makes them speed up the development and production process constantly. One of the reasons is the market globalization. In many countries extremely low production costs are possible. The prize is o en a violation of ethical and safety principles that is unacceptable in most European countries. One of the possibilities how to fi ght with such a kind of production is to maintain a technological lead. Therefore it is necessary to focus on methods which increase the development and production process effi ciency.An integral part of development of many products is their design. It is well known that the process includes initial design phase in a form of sketche...

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Section: Methods and Resourcesmentioning

confidence: 99%

Augmented reality usage for prototyping speed up

Šťastný¹,

Procházka²,

Koubek³

et al. 2014

Acta Univ. Agric. Silvic. Mendelianae Brun.

View full text Add to dashboard Cite

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“…[17] In addition to these corner extraction process, a number of methods have been studied [18]; as method etc. for detecting the corner by locally splitting the contour map of the image, by analyzing the curvature information if the distribution of the contrast has the form of curvature [18][19][20][21], by using a symmetric analysis. [22][23], and by using a video image registration algorithm based on corner point detection and feature point integration.…”

Section: Introductionmentioning

confidence: 99%

Rearranged DCT Feature Analysis Based on Corner Patches for CBIR (contents based image retrieval)

Lee¹,

Park²,

An³

et al. 2016

The Transactions of The Korean Institute of Electrical Engineer

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-In modern society, creation and distribution of multimedia contents is being actively conducted. These multimedia information have come out the enormous amount daily, the amount of data is also large enough it can't be compared with past text information. Since it has been increased for a need of the method to efficiently store multimedia information and to easily search the information, various methods associated therewith have been actively studied. In particular, image search methods for finding what you want from the video database or multiple sequential images, have attracted attention as a new field of image processing. Image retrieval method to be implemented in this paper, utilizes the attribute of corner patches based on the corner points of the object, for providing a new method of efficient and robust image search. After detecting the edge of the object within the image, the straight lines using a Hough transformation is extracted. A corner patches is formed by defining the extracted intersection of the straight line as a corner point. After configuring the feature vectors with patches rearranged, the similarity between images in the database is measured. Finally, for an accurate comparison between the proposed algorithm and existing algorithms, the recall precision rate, which has been widely used in content-based image retrieval was used to measure the performance evaluation. For the image used in the experiment, it was confirmed that the image is detected more accurately in the proposed method than the conventional image retrieval methods

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“…Comer detection, together with edge extraction are among the most popular feature extraction tasks as is well established by the abundant bibhography in image processing [1][2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Correlation based rotation-invariant corner detector

Mazzaferri¹,

Ledesma²,

Wetter³

et al. 2008

AIP Conference Proceedings

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Abstract. In this work we introduce a new approach for corner extraction. The method that allows the corner extraction with rotation invariance is composed by a spiral phase function and a binary amplitude. The designed function can be easily implemented as a filter for a Vander Lugt-like optical correlator A final image obtained with the detector presents intensity peaks in each corner location. Numerical simulation has been performed on a set of synthetic scenes, modulated either in amplitude or phase. Results that show the very good performance of the method are shown.

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Performance assessment of feature detection algorithms: a methodology and case study on corner detectors

Cited by 64 publications

References 22 publications

Augmented reality usage for prototyping speed up

Augmented reality usage for prototyping speed up

Rearranged DCT Feature Analysis Based on Corner Patches for CBIR (contents based image retrieval)

Correlation based rotation-invariant corner detector

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