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Visual attention detection method and device based on lateral suppression

A technology of visual attention and detection methods, applied in the field of computer vision, can solve the problems of reducing the effectiveness and practicability of the attention mechanism of computer vision, and cannot completely simulate the visual attention mechanism of the human brain.

Active Publication Date: 2018-07-20
INST OF AUTOMATION CHINESE ACAD OF SCI
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Problems solved by technology

At present, the visual attention mechanism in the field of computer vision technology mainly includes the selective attention mechanism and the salient target attention mechanism, but neither of these two attention mechanisms can completely simulate the visual attention mechanism of the human brain, which reduces the effectiveness and effectiveness of the computer vision attention mechanism. Practicality

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  • Visual attention detection method and device based on lateral suppression
  • Visual attention detection method and device based on lateral suppression
  • Visual attention detection method and device based on lateral suppression

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Embodiment Construction

[0078] Preferred embodiments of the present invention are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention, and are not intended to limit the protection scope of the present invention.

[0079] Biocognitive neuroscience shows that there are various connections in the brain, such as feedforward, feedback and lateral connections. When a visual input is given, the activated neurons in the brain will first compete with each other, and the result is that some neurons win, and some neurons fail or are in a disadvantaged state. This kind of competition is carried out layer by layer, and finally reaches the semantic layer. draw a preliminary conclusion. Based on preliminary conclusions, the brain realigns and organizes information to support the conclusions reached. Cognitive psychology describes this process as: information flows t...

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Abstract

The invention, which relates to the field of computer vision technology, in particular provides a visual attention detection method and device based on lateral suppression, thereby improving the effectiveness and practicability of the computer visual attention mechanism. The visual attention detection method comprises: an image type of a target image is obtained; feedback information received by each activation function neuron is obtained; according to the feedback information, whether the corresponding activation function neuron needs to be turned off is determined; according to the determination result, the corresponding activation function neuron is turned off and then a response value of the activation function neuron is normalized to obtain a selective attention result graph; and theselective attention result graph is normalized to obtain a saliency target detection result graph. According to the invention, on the basis of the convolutional neural network, the information of thetarget object is detected by using feedforward and feedback information of the convolutional neural network. Besides, the visual attention detection device can be implemented to realize the method.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a method and device for detecting visual attention based on lateral inhibition. Background technique [0002] The visual attention mechanism can guide the human eye to focus on significant areas in massive data, and allocate resources to prioritize important areas, so that humans can quickly find areas of interest from complex scenes. Specifically, when the human eye receives a large amount of visual information, the human brain can filter out a small number of important information that humans are interested in, so as to process the information preferentially. At present, the visual attention mechanism in the field of computer vision technology mainly includes the selective attention mechanism and the salient target attention mechanism, but neither of these two attention mechanisms can completely simulate the visual attention mechanism of the human brain, which reduces t...

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Application Information

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IPC IPC(8): G06K9/00G06K9/32G06N3/04G06N3/08
CPCG06N3/082G06N3/084G06V20/00G06V10/25G06V2201/07G06N3/045
Inventor 谭铁牛王亮黄永祯曹春水
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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