research-article

Perceptual modeling in the problem of active object recognition in visual scenes

Authors:

Iván González-Díaz,

Jenny Benois-PineauAuthors Info & Claims

Pattern Recognition, Volume 56, Issue C

Pages 129 - 141

https://doi.org/10.1016/j.patcog.2016.03.007

Published: 01 August 2016 Publication History

Abstract

Incorporating models of human perception into the process of scene interpretation and object recognition in visual content is a strong trend in computer vision. In this paper we tackle the modeling of visual perception via automatic visual saliency maps for object recognition. Visual saliency represents an efficient way to drive the scene analysis towards particular areas considered 'of interest' for a viewer and an efficient alternative to computationally intensive sliding window methods for object recognition. Using saliency maps, we consider biologically inspired independent paths of central and peripheral vision and apply them to fundamental steps of the so-called Bag-of-Words (BoW) paradigm, such as features sampling, pooling and encoding. Our proposal has been evaluated addressing the challenging task of active object recognition, and the results show that our method not only improves the baselines, but also achieves state-of-the-art performance in various datasets at very competitive computational times. HighlightsPerceptual model that incorporates visual attention to the problem of active object recognition.Modeling of foveal and peripheral pathways in retina.Saliency-based non-uniform feature sampling in a variable-resolution space.Saliency-sensitive Coding of features.Saliency-based Pooling of features.

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Cited By

Diko AAvola DCascio MCinque L(2024)ReViTPattern Recognition10.1016/j.patcog.2024.110853156:COnline publication date: 18-Nov-2024
https://dl.acm.org/doi/10.1016/j.patcog.2024.110853
Obeso ABenois-Pineau JGarcía Vázquez MAcosta A(2022)Visual vs internal attention mechanisms in deep neural networks for image classification and object detectionPattern Recognition10.1016/j.patcog.2021.108411123:COnline publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1016/j.patcog.2021.108411
Parikh AKoch MBlada TBuerger S(2020)Rapid Autonomous Semantic Mapping2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS45743.2020.9341564(6156-6163)Online publication date: 24-Oct-2020
https://dl.acm.org/doi/10.1109/IROS45743.2020.9341564
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Perceptual modeling in the problem of active object recognition in visual scenes
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks

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cover image Pattern Recognition

Pattern Recognition Volume 56, Issue C

August 2016

184 pages

ISSN:0031-3203

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Copyright © Elsevier Ltd.

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Elsevier Science Inc.

United States

Publication History

Published: 01 August 2016

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Cited By

Diko AAvola DCascio MCinque L(2024)ReViTPattern Recognition10.1016/j.patcog.2024.110853156:COnline publication date: 18-Nov-2024
https://dl.acm.org/doi/10.1016/j.patcog.2024.110853
Obeso ABenois-Pineau JGarcía Vázquez MAcosta A(2022)Visual vs internal attention mechanisms in deep neural networks for image classification and object detectionPattern Recognition10.1016/j.patcog.2021.108411123:COnline publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1016/j.patcog.2021.108411
Parikh AKoch MBlada TBuerger S(2020)Rapid Autonomous Semantic Mapping2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS45743.2020.9341564(6156-6163)Online publication date: 24-Oct-2020
https://dl.acm.org/doi/10.1109/IROS45743.2020.9341564
Obeso ABenois-Pineau JVázquez MAcosta A(2019)Saliency-based selection of visual content for deep convolutional neural networksMultimedia Tools and Applications10.1007/s11042-018-6515-278:8(9553-9576)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.1007/s11042-018-6515-2
Wang MLuo CNi BYuan JWang JYan S(2018)First-Person Daily Activity Recognition With Manipulated Object Proposals and Non-Linear Feature FusionIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2017.271681928:10(2946-2955)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1109/TCSVT.2017.2716819
Obeso AVázquez MAcosta ABenois-Pineau J(2017)ConnoisseurProceedings of the 15th International Workshop on Content-Based Multimedia Indexing10.1145/3095713.3095730(1-7)Online publication date: 19-Jun-2017
https://dl.acm.org/doi/10.1145/3095713.3095730
Li AChen Z(2017)Individual trait oriented scanpath prediction for visual attention analysis2017 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2017.8296982(3745-3749)Online publication date: 17-Sep-2017
https://dl.acm.org/doi/10.1109/ICIP.2017.8296982
Gmez LKaratzas D(2017)TextProposalsPattern Recognition10.1016/j.patcog.2017.04.02770:C(60-74)Online publication date: 1-Oct-2017
https://dl.acm.org/doi/10.1016/j.patcog.2017.04.027

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