Visual constructed representations for object recognition and detection

Yasuomi D. Sato; Yasutaka Kuriya

doi:10.1007/978-3-642-24965-5_69

Visual constructed representations for object recognition and detection

Yasuomi D. Sato, Yasutaka Kuriya

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

3 Citations (Scopus)

Abstract

We propose a neurally inspired model for parallel visual process for recognition and detection. This model is based on the Gabor feature explicit representation construction. An input image is decomposed of different scale features through the low-pass filter. Nevertheless, recycling and overlapping again the scale features, the most likely object stored in memory can be detected on the input image. This is done by scale feature correspondence finding. Simultaneously, Gabor feature representations stored in memory are also constructed by selecting the most similar scale features to the input. We also test a recognition ability of our model, using a number of facial images of different persons. Distortion invariant recognition is also demonstrated.

Original language	English
Title of host publication	Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings
Pages	611-620
Number of pages	10
Edition	PART 3
DOIs	https://doi.org/10.1007/978-3-642-24965-5_69
Publication status	Published - 2011
Externally published	Yes
Event	18th International Conference on Neural Information Processing, ICONIP 2011 - Shanghai, China Duration: 2011 Nov 13 → 2011 Nov 17

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 3
Volume	7064 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	18th International Conference on Neural Information Processing, ICONIP 2011
Country/Territory	China
City	Shanghai
Period	11/11/13 → 11/11/17

Keywords

Gabor Feature Representation Construction
Visual Object/Face Recognition and Detection

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-24965-5_69

Cite this

Sato, Y. D., & Kuriya, Y. (2011). Visual constructed representations for object recognition and detection. In Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings (PART 3 ed., pp. 611-620). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7064 LNCS, No. PART 3). https://doi.org/10.1007/978-3-642-24965-5_69

Visual constructed representations for object recognition and detection. / Sato, Yasuomi D.; Kuriya, Yasutaka.

Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings. PART 3. ed. 2011. p. 611-620 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7064 LNCS, No. PART 3).

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

Sato, YD & Kuriya, Y 2011, Visual constructed representations for object recognition and detection. in Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings. PART 3 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 7064 LNCS, pp. 611-620, 18th International Conference on Neural Information Processing, ICONIP 2011, Shanghai, China, 11/11/13. https://doi.org/10.1007/978-3-642-24965-5_69

Sato YD, Kuriya Y. Visual constructed representations for object recognition and detection. In Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings. PART 3 ed. 2011. p. 611-620. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). https://doi.org/10.1007/978-3-642-24965-5_69

Sato, Yasuomi D. ; Kuriya, Yasutaka. / Visual constructed representations for object recognition and detection. Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings. PART 3. ed. 2011. pp. 611-620 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).

@inproceedings{2e008078d0f54dbfac19fa5837cb10ec,

title = "Visual constructed representations for object recognition and detection",

abstract = "We propose a neurally inspired model for parallel visual process for recognition and detection. This model is based on the Gabor feature explicit representation construction. An input image is decomposed of different scale features through the low-pass filter. Nevertheless, recycling and overlapping again the scale features, the most likely object stored in memory can be detected on the input image. This is done by scale feature correspondence finding. Simultaneously, Gabor feature representations stored in memory are also constructed by selecting the most similar scale features to the input. We also test a recognition ability of our model, using a number of facial images of different persons. Distortion invariant recognition is also demonstrated.",

keywords = "Gabor Feature Representation Construction, Visual Object/Face Recognition and Detection",

author = "Sato, {Yasuomi D.} and Yasutaka Kuriya",

year = "2011",

doi = "10.1007/978-3-642-24965-5_69",

language = "English",

isbn = "9783642249648",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 3",

pages = "611--620",

booktitle = "Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings",

edition = "PART 3",

note = "18th International Conference on Neural Information Processing, ICONIP 2011 ; Conference date: 13-11-2011 Through 17-11-2011",

}

TY - GEN

T1 - Visual constructed representations for object recognition and detection

AU - Sato, Yasuomi D.

AU - Kuriya, Yasutaka

PY - 2011

Y1 - 2011

N2 - We propose a neurally inspired model for parallel visual process for recognition and detection. This model is based on the Gabor feature explicit representation construction. An input image is decomposed of different scale features through the low-pass filter. Nevertheless, recycling and overlapping again the scale features, the most likely object stored in memory can be detected on the input image. This is done by scale feature correspondence finding. Simultaneously, Gabor feature representations stored in memory are also constructed by selecting the most similar scale features to the input. We also test a recognition ability of our model, using a number of facial images of different persons. Distortion invariant recognition is also demonstrated.

AB - We propose a neurally inspired model for parallel visual process for recognition and detection. This model is based on the Gabor feature explicit representation construction. An input image is decomposed of different scale features through the low-pass filter. Nevertheless, recycling and overlapping again the scale features, the most likely object stored in memory can be detected on the input image. This is done by scale feature correspondence finding. Simultaneously, Gabor feature representations stored in memory are also constructed by selecting the most similar scale features to the input. We also test a recognition ability of our model, using a number of facial images of different persons. Distortion invariant recognition is also demonstrated.

KW - Gabor Feature Representation Construction

KW - Visual Object/Face Recognition and Detection

UR - http://www.scopus.com/inward/record.url?scp=81855198080&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=81855198080&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-24965-5_69

DO - 10.1007/978-3-642-24965-5_69

M3 - Conference contribution

AN - SCOPUS:81855198080

SN - 9783642249648

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 611

EP - 620

BT - Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings

T2 - 18th International Conference on Neural Information Processing, ICONIP 2011

Y2 - 13 November 2011 through 17 November 2011

ER -

Visual constructed representations for object recognition and detection

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this