A mixed model based on shape context and spark for sketch based image retrieval

Willy Puenternan Fernández; César A. Beltrán Castañón

doi:10.1007/978-3-030-11680-4_32

A mixed model based on shape context and spark for sketch based image retrieval

Willy Puenternan Fernández, César A. Beltrán Castañón

Pontifical Catholic Univ. of Peru

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Nowadays, information is not limited to textual representation but takes several other forms such as sketch-based image retrieval, where the user draws a query, and the system retrieves the most similar images. In this work we present a mixed approach combining shape context and Spark features, previously we had applied the Bag-of-Features strategy to select regions of interest, achieving significant improvement in effectiveness of the retrieval task. Our method works as a local strategy for key-points detection. Results are very auspicious, and we show different experiments conducted to demonstrate our proposed methodology. The highlight of this paper is the step-by-step description of the methodology to create a framework for sketch-based image retrieval.

Original language	English
Title of host publication	Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings
Editors	Denisse Muñante, Hugo Alatrista-Salas, Juan Antonio Lossio-Ventura
Publisher	Springer Verlag
Pages	341-348
Number of pages	8
ISBN (Print)	9783030116798
DOIs	https://doi.org/10.1007/978-3-030-11680-4_32
State	Published - 2019
Event	5th International Conference on Information Management and Big Data, SIMBig 2018 - Lima, Peru Duration: 3 Sep 2018 → 5 Sep 2018

Publication series

Name	Communications in Computer and Information Science
Volume	898
ISSN (Print)	1865-0929

Conference

Conference	5th International Conference on Information Management and Big Data, SIMBig 2018
Country/Territory	Peru
City	Lima
Period	3/09/18 → 5/09/18

Keywords

Bag-of-features
SBIR
Shape context
Spark feature

Access to Document

10.1007/978-3-030-11680-4_32

Cite this

Puenternan Fernández, W., & Beltrán Castañón, C. A. (2019). A mixed model based on shape context and spark for sketch based image retrieval. In D. Muñante, H. Alatrista-Salas, & J. A. Lossio-Ventura (Eds.), Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings (pp. 341-348). (Communications in Computer and Information Science; Vol. 898). Springer Verlag. https://doi.org/10.1007/978-3-030-11680-4_32

Puenternan Fernández, Willy ; Beltrán Castañón, César A. / A mixed model based on shape context and spark for sketch based image retrieval. Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings. editor / Denisse Muñante ; Hugo Alatrista-Salas ; Juan Antonio Lossio-Ventura. Springer Verlag, 2019. pp. 341-348 (Communications in Computer and Information Science).

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title = "A mixed model based on shape context and spark for sketch based image retrieval",

abstract = "Nowadays, information is not limited to textual representation but takes several other forms such as sketch-based image retrieval, where the user draws a query, and the system retrieves the most similar images. In this work we present a mixed approach combining shape context and Spark features, previously we had applied the Bag-of-Features strategy to select regions of interest, achieving significant improvement in effectiveness of the retrieval task. Our method works as a local strategy for key-points detection. Results are very auspicious, and we show different experiments conducted to demonstrate our proposed methodology. The highlight of this paper is the step-by-step description of the methodology to create a framework for sketch-based image retrieval.",

keywords = "Bag-of-features, SBIR, Shape context, Spark feature",

author = "{Puenternan Fern{\'a}ndez}, Willy and {Beltr{\'a}n Casta{\~n}{\'o}n}, {C{\'e}sar A.}",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 5th International Conference on Information Management and Big Data, SIMBig 2018 ; Conference date: 03-09-2018 Through 05-09-2018",

year = "2019",

doi = "10.1007/978-3-030-11680-4_32",

language = "English",

isbn = "9783030116798",

series = "Communications in Computer and Information Science",

publisher = "Springer Verlag",

pages = "341--348",

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booktitle = "Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings",

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Puenternan Fernández, W & Beltrán Castañón, CA 2019, A mixed model based on shape context and spark for sketch based image retrieval. in D Muñante, H Alatrista-Salas & JA Lossio-Ventura (eds), Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings. Communications in Computer and Information Science, vol. 898, Springer Verlag, pp. 341-348, 5th International Conference on Information Management and Big Data, SIMBig 2018, Lima, Peru, 3/09/18. https://doi.org/10.1007/978-3-030-11680-4_32

A mixed model based on shape context and spark for sketch based image retrieval. / Puenternan Fernández, Willy; Beltrán Castañón, César A.
Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings. ed. / Denisse Muñante; Hugo Alatrista-Salas; Juan Antonio Lossio-Ventura. Springer Verlag, 2019. p. 341-348 (Communications in Computer and Information Science; Vol. 898).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A mixed model based on shape context and spark for sketch based image retrieval

AU - Puenternan Fernández, Willy

AU - Beltrán Castañón, César A.

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N2 - Nowadays, information is not limited to textual representation but takes several other forms such as sketch-based image retrieval, where the user draws a query, and the system retrieves the most similar images. In this work we present a mixed approach combining shape context and Spark features, previously we had applied the Bag-of-Features strategy to select regions of interest, achieving significant improvement in effectiveness of the retrieval task. Our method works as a local strategy for key-points detection. Results are very auspicious, and we show different experiments conducted to demonstrate our proposed methodology. The highlight of this paper is the step-by-step description of the methodology to create a framework for sketch-based image retrieval.

AB - Nowadays, information is not limited to textual representation but takes several other forms such as sketch-based image retrieval, where the user draws a query, and the system retrieves the most similar images. In this work we present a mixed approach combining shape context and Spark features, previously we had applied the Bag-of-Features strategy to select regions of interest, achieving significant improvement in effectiveness of the retrieval task. Our method works as a local strategy for key-points detection. Results are very auspicious, and we show different experiments conducted to demonstrate our proposed methodology. The highlight of this paper is the step-by-step description of the methodology to create a framework for sketch-based image retrieval.

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KW - SBIR

KW - Shape context

KW - Spark feature

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Puenternan Fernández W, Beltrán Castañón CA. A mixed model based on shape context and spark for sketch based image retrieval. In Muñante D, Alatrista-Salas H, Lossio-Ventura JA, editors, Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings. Springer Verlag. 2019. p. 341-348. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-11680-4_32

A mixed model based on shape context and spark for sketch based image retrieval

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