Description: 视觉注意力模型，寻找感兴趣区域，模仿人眼找出最感兴趣的区域，再找出第二感兴趣的区域，以此类推-Visual attention model to find the region of interest, to imitate the human eye to identify the most interesting region, and then find the second region of interest, and so on Platform: |
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Author:panda |
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Description: 该文件夹包括代码及其对应的论文。其作用在于模拟人类视觉系统的生理特性--视觉注意机制，按照人眼观察外界的方式，检测视觉显著性物体和区域，并阐述了显著性区域的显著性密度和尺度之间的关系，可应用于生物视觉模拟、视觉目标检测、视觉目标跟踪、视觉智能监控，以及视觉生理学和视觉心理学等的研究中。-This document contains codes and the corresponding paper. The aim is to simulate a physiological characteristic of human visual system called visual attention mechanism. The code is used to detect salient objects or regions following the way human eye observes the world. The relation between density and scale of salient object/region is described. It has found widespread use in numerous applications such as biological vision simulation, visual object detection, visual object tracking, visual intelligent surveillance, visual physiological, and visual psychology. Platform: |
Size: 4237312 |
Author:朱亮亮 |
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Description: 基于matlab利用视觉注意机制模型和图像分割技术提取感兴趣区域-The use of visual attention mechanism based on matlab image segmentation technique to extract the model and region of interest Platform: |
Size: 1175552 |
Author:陈林 |
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Description: 本文主要研究海面运动船只的识别与跟踪技术。首先概述了海上运动目标检测和跟踪的研究现状；对目前主要的显著区域提取、运动目标识别和跟踪方法进行了简要概述；提出了基于视觉注意和HOG特征相融合的海上船只目标检测方法；利用多特征融合的粒子滤波算法对运动目标进行了跟踪。-This paper studies the sea sport vessel identification and tracking technology. First, an overview of maritime moving target detection and tracking research status right now the main salient region extraction, moving target identification and tracking methods are briefly outlined proposed based on visual attention and HOG feature fusion of sea vessels target detection method utilization multi-feature fusion particle filter algorithm to track the moving target. Platform: |
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Author:wenping |
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Description: Digital watermark embeds informa-
tion bits into digital cover such as images and
videos to prove the creator’s ownership of his
work. In this paper, we propose a robust image
watermark algorithm based on a generative
adversarial network. This model includes two
modules, generator and adversary. Generator
is mainly used to generate images embedded
with watermark, and decode the image dam-
aged by noise to obtain the watermark. Adver-
sary is used to discriminate whether the image
is embedded with watermark and damage the
image by noise. Based on the model Hidden
(hiding data with deep networks), we add a
high-pass filter in front of the discriminator,
making the watermark tend to be embedded in
the mid-frequency region of the image. Since
the human visual system pays more attention
to the central area of the image, we give a
higher weight to the image center region, and
a lower weight to the edge region when calcu-
lating the loss between cover and embedded
image. The watermarked image obtained by
this scheme has a better visual performance.
Experimental results show that the proposed
architecture is more robust against noise
interference compared with the state-of-art
schemes. Platform: |
Size: 704508 |
Author:bamzi334 |
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Search - visual attention region