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Treffer: Visual saliency based approach to object detection in computer vision systems: Real life applications

Title:
Visual saliency based approach to object detection in computer vision systems: Real life applications
Authors:
Kachurka, V., Madani, K., K., Sabourin, C., Golovko, V.
Contributors:
SYNAPSE, Laboratoire Images, Signaux et Systèmes Intelligents (LISSI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)
Source:
Proc. of the 8th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems. :239-244
Publisher Information:
CCSD, 2015.
Publication Year:
2015
Collection:
collection:LISSI
collection:UPEC
collection:TEST-SEBASTIEN2
Subject Terms:
visual saliency, Center-surround antagonism, Evolutionary optimization, Eye fixation problem, Autonomous object detection, [INFO.INFO-CV]Computer Science [cs], Computer Vision and Pattern Recognition [cs.CV], [SCCO.COMP]Cognitive science, Computer science
Subject Geographic:
Warsaw, Poland
Original Identifier:
HAL: hal-01568465
Document Type:
Konferenz conferenceObject<br />Conference papers
Language:
English
Relation:
info:eu-repo/semantics/altIdentifier/doi/10.1109/IDAACS.2015.7340736
DOI:
10.1109/IDAACS.2015.7340736
Availability:
https://hal.science/hal-01568465
Accession Number:
edshal.hal.01568465v1
Database:
HAL

Weitere Informationen

A hybrid approach combining object detection in image and eye-fixation probability map calculation is proposed. This approach has been evaluated on human-like eye-fixation prediction benchmark. Experimental results show viability and efficiency of this approach providing comparison with state-of-art algorithms. The proposed approach has been applied to a real-world application of detection of fire-and-smoke in natural outdoor environment.