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Logical methods of object recognition on satellite images using spatial constraints
A logical approach to object recognition on image is proposed. The main ...
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The Effect of Top-Down Attention in Occluded Object Recognition
This study is concerned with the top-down visual processing benefit in t...
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Multiple Moving Object Recognitions in video based on Log Gabor-PCA Approach
Object recognition in the video sequence or images is one of the sub-fie...
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Suspicious Object Recognition Method in Video Stream Based on Visual Attention
We propose a state of the art method for intelligent object recognition ...
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Towards the Design of an End-to-End Automated System for Image and Video-based Recognition
Over many decades, researchers working in object recognition have longed...
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Abnormal Object Recognition: A Comprehensive Study
When describing images, humans tend not to talk about the obvious, but r...
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Ball-Scale Based Hierarchical Multi-Object Recognition in 3D Medical Images
This paper investigates, using prior shape models and the concept of bal...
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Latent Bi-constraint SVM for Video-based Object Recognition
We address the task of recognizing objects from video input. This important problem is relatively unexplored, compared with image-based object recognition. To this end, we make the following contributions. First, we introduce two comprehensive datasets for video-based object recognition. Second, we propose Latent Bi-constraint SVM (LBSVM), a maximum-margin framework for video-based object recognition. LBSVM is based on Structured-Output SVM, but extends it to handle noisy video data and ensure consistency of the output decision throughout time. We apply LBSVM to recognize office objects and museum sculptures, and we demonstrate its benefits over image-based, set-based, and other video-based object recognition.
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