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This paper investigates how well real-world events can be characterized by visual features detected in related images posted on social media, using state-of-the-art computer vision methods for object detection and classification. Over 48k images from four different events have been processed to detect objects of different types using convolutional neural networks (CNNs) and cascaded classifiers. Based...
In this paper, we present a novel human detection method by devising a saliency framework on visual attention HOG features for infrared thermal imaging cameras. The proposed approach extends the saliency map by including the representation not only spatial features but also gaze distribution features. During thermal videos, the developed framework consists several computational stages: (a) the regions...
Due to the intrinsic long-tailed distribution of objects in the real world, we are unlikely to be able to train an object recognizer/detector with many visual examples for each category. We have to share visual knowledge between object categories to enable learning with few or no training examples. In this paper, we show that local object similarity information--statements that pairs of categories...
Video data is becoming increasingly important in many commercial and scientific areas with the advent of applications such as digital broadcasting, video-conferencing and multimedia processing tools, and with the development of the hardware and communications infrastructure necessary to support visual applications. The objective of this work is to propose a method for event detection in a video stream...
Online shopping is becoming more and more popular for a number of reasons; prices are often lower online, you don't have to queue up in busy shops and you can buy almost any product imaginable with just a few clicks of your mouse. But the general problems of shopping Web site is that, most of the existing online shops list products based on keywords. As the inherent limitation, keyword browsing makes...
This paper presents a new neural network to perform the visual pattern classification task. The neural network is called I-PyraNet which is a hybrid implementation of the PyraNet and the concepts of the inhibitory fields. In order to improve the results obtained by this neural network, it is also presented the 2-D Gabor filter. Furthermore, both, the neural network and the filter, are applied over...
This paper proposes an improvement of advanced driver assistance system based on saliency estimation of road signs. After a road sign detection stage, its saliency is estimated using a SVM learning. A model of visual saliency linking the size of an object and a size-independent saliency is proposed. An eye tracking experiment in context close to driving proves that this computational evaluation of...
Visual category recognition is challenging in computer vision and has several problem. Some of problems on visual category recognition are variance to the object instance position and background clutter. In this paper, we propose method select region of interest (ROI) in training and recognizing automatically. This provide invariance to object instance position and removing background clutter. In...
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