A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Robust Real-Time Face Detection
International Journal of Computer Vision
Integral Histogram: A Fast Way To Extract Histograms in Cartesian Spaces
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Integrated Model of Top-Down and Bottom-Up Attention for Optimizing Detection Speed
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
An unsupervised method for clustering images based on their salient regions of interest
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Seam carving for content-aware image resizing
ACM SIGGRAPH 2007 papers
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Active-GNG: model acquisition and tracking in cluttered backgrounds
VNBA '08 Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Illumination-robust variational optical flow with photometric invariants
Proceedings of the 29th DAGM conference on Pattern recognition
Salient region detection and segmentation
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Curious George: An Integrated Visual Search Platform
CRV '10 Proceedings of the 2010 Canadian Conference on Computer and Robot Vision
Is bottom-up attention useful for object recognition?
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Learning to Detect a Salient Object
IEEE Transactions on Pattern Analysis and Machine Intelligence
Surveillance and human-computer interaction applications of self-growing models
Applied Soft Computing
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Hybrid Salient Object Extraction Approach with Automatic Estimation of Visual Attention Scale
SITIS '11 Proceedings of the 2011 Seventh International Conference on Signal Image Technology & Internet-Based Systems
A flexible edge matching technique for object detection in dynamic environment
Applied Intelligence
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Existing object recognition techniques often rely on human labeled data conducting to severe limitations to design a fully autonomous machine vision system. In this work, we present an intelligent machine vision system able to learn autonomously individual objects present in real environment. This system relies on salient object detection. In its design, we were inspired by early processing stages of human visual system. In this context we suggest a novel fast algorithm for visually salient object detection, robust to real-world illumination conditions. Then we use it to extract salient objects which can be efficiently used for training the machine learning-based object detection and recognition unit of the proposed system. We provide results of our salient object detection algorithm on MSRA Salient Object Database benchmark comparing its quality with other state-of-the-art approaches. The proposed system has been implemented on a humanoid robot, increasing its autonomy in learning and interaction with humans. We report and discuss the obtained results, validating the proposed concepts.