检索结果-内蒙古大学图书馆

Locating sea-sky line in infrared image based on complex degree calculation

Locating sea-sky line in infrared image based on complex deg...

MIPPR 2009 - multispectral Image Acquisition and processing: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Wang, Peng Tian, Jinwen Gao, Chenqiang State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478054

Research on the location of sea-sky line under infrared complicated sea-sky background has the important value to improve the capability of far target recognition. In a real sea-sky background infrared image, the sky and the sea normally appear in the form of different changes of grey-level on account of their different infrared radiation and reflection characteristics. So we can use the background complex degree to differentiate between the sky region and the sea region. In our method, an operator is employed to calculate the background complex degree of image. By filtering original infrared image with the operator, the grey-level contrast between the sky region and the sea region can be stronger than original image. After the complex degree calculation, the edge detection with only row directional gradient and Hough transform are utilized in succession, the sea-sky line can be located. Some typical sea-sky background infrared images are selected to validate our proposed method. The experimental results indicate that our sea-sky line location method is robust. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Hough transforms

来源：评论

学校读者我要写书评

暂无评论

3D hand pose and shape estimation from monocular RGB via efficient 2D cues

引用

Computational Visual Media 2024年第1期10卷 79-96页

作者： Fenghao Zhang Lin Zhao Shengling Li Wanjuan Su Liman Liu Wenbing Tao Hubei Key Laboratory of Medical Information Analysis and Tumor Diagnosis&Treatment School of Biomedical EngineeringSouth Central Minzu UniversityWuhan430074China National Key Laboratory of Science and Technology of Multi-spectral Information Processing School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan430074China

Estimating 3D hand shape from a single-view RGB image is important for many ***,the diversity of hand shapes and postures,depth ambiguity,and occlusion may result in pose errors and noisy hand *** full use of 2D cues such as 2D pose can effectively improve the quality of 3D human hand shape *** this paper,we use 2D joint heatmaps to obtain spatial details for robust pose *** also introduce a depth-independent 2D mesh to avoid depth ambiguity in mesh regression for efficient hand-image *** method has four cascaded stages:2D cue extraction,pose feature encoding,initial reconstruction,and reconstruction ***,we first encode the image to determine semantic features during 2D cue extraction;this is also used to predict hand joints and for ***,during the pose feature encoding stage,we use a hand joints encoder to learn spatial information from the joint ***,a coarse 3D hand mesh and 2D mesh are obtained in the initial reconstruction step;a mesh squeeze-and-excitation block is used to fuse different hand features to enhance perception of 3D hand ***,a global mesh refinement stage learns non-local relations between vertices of the hand mesh from the predicted 2D mesh,to predict an offset hand mesh to fine-tune the reconstruction *** and qualitative results on the FreiHAND benchmark dataset demonstrate that our approach achieves state-of-the-art performance.

关键词： hand 3D reconstruction deep learning image features 3D mesh

来源：评论

学校读者我要写书评

暂无评论

Semantic Segmentation Algorithm of Remote Sensing Images Based on Improved Panoptic

Semantic Segmentation Algorithm of Remote Sensing Images Bas...

引用

2022 International Conference on Automation, Robotics and Computer Engineering, ICARCE 2022

作者： Zheng, Tong Liu, Liu Chen, Qimeng Chen, Zhong Yu, Longji Zhao, Zeyu Huazhong University of Science and Technology National Key Laboratory of Science and Technology on Multi-Spectral Information Processing Wuhan China

ISBN: (纸本)9781665475488

Semantic segmentation of images can play an important role in land use, building extraction, road extraction and vehicle detection using remote sensing images. In the scenario of applying Panoptic FPN algorithm for remote sensing images, we found that the decoder of this algorithm is not robust in feature extraction and cannot do weighted enhancement of key spaces and channels, and its encoder loses a lot of high-dimensional semantic features when simply fusing semantic information at all levels by simple addition. To address these two problems, we propose the Se-Resnext encoder based on the attention mechanism and the Concat-based feature fusion mechanism, respectively, and verify the effectiveness of the methods through experiments. The accuracy of semantic segmentation is improved in both suichang dataset and posdam dataset. © 2022 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

A flower algorithm for autonomous star pattern recognition

A flower algorithm for autonomous star pattern recognition

引用

作者： Gong, Jiaqi Ma, Jie Tian, Jinwen State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781563479694

An autonomous star pattern recognition algorithm is proposed herein that is effectively stable against the higher level noise than other algorithms. In simulations using an 8×8 degree field of view (FOV), the algorithm identifies the correct section of sky on 99.5% of the sensor orientations where spatial accuracy of the imaged star is 2 pixels (0.03 degree) in standard deviation and the apparent brightness deviate by 0.5 units' stellar magnitude. The achievable performance comes from the generation of the Flower-code pattern, which includes angular distances and circular angles as the characteristics of the pivot star. The angular distances are used for initial lookup table match. Moreover, the circular angles are adopted for the cyclic dynamic match between the sensor pattern and the pattern candidates from the initial match. And also, the performance is demonstrated via a comparison study on two published algorithms. Copyright © 2009 by the American Institute of Aeronautics and Astronautics, Inc.

关键词： Table lookup

来源：评论

学校读者我要写书评

暂无评论

Research on Adaptation Criteria Generation based on Large Data Mining 7

Research on Adaptation Criteria Generation based on Large Da...

引用

2016 IEEE Chinese Guidance, Navigation and Control Conference (IEEE CGNCC2016)

作者： Yun Hong-quan XU Li DOU Hao MING De-lie National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute State Key Laboratory for Multi-spectral Information Processing Technologies School of AutomationHuazhong University of Science and Technology

ISBN: (纸本)9781467383196

This paper performs research on adaptation analysis based on large amount of multi-source remote sensing *** view of different demands from different task background,the research is firstly focused on how to analyze the data in computer *** achieve this,the feature parameters of target areas are extracted from different target area geographic *** combination of ORACLE database engine,data mining technology is used to carry out the target area adaptation assessment,and extract corresponding adaptation *** test the trained adaptation criteria on multi-source geographic information data of different target *** results show that the resulting criterion has certain coincidence rate and robustness.

关键词： image Research on Adaptation Criteria Generation based on Large Data Mining

来源：评论

学校读者我要写书评

暂无评论

SVM based classification of moving objects in video

SVM based classification of moving objects in video

引用

MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Sun, Airong Bai, Min Tan, Yihua Tian, Jinwen State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Patter Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

In this paper, a classification method of four moving objects including vehicle, human, motorcycle and bicycle in surveillance video was presented by using machine learning idea. The method can be described as three steps: feature selection, training of Support Vector Machine(SVM) classifier and performance evaluation. Firstly, a feature vector to represent the discriminabilty of an object is described. From the profile of object, the ratio of width to height and trisection ratio of width to height are firstly adopted as the distinct feature. Moreover, we use external rectangle to approximate the object mask, which leads to a feature of rectangle degree standing for the ratio between the area of object to the area of external rectangle. To cope with the invariance to scale, rotation and so on, Hu moment invariants, Fourier descriptor and dispersedness were extracted as another kind of features. Secondly, a multi-class classifier were designed based on two-class SVM. The idea behind the classifier structure is that the multi-class classification can be converted to the combination of two-class classification. For our case, the final classification is the vote result of six twoclass classifier. Thirdly, we determine the precise feature selection by experiments. According to the classification result, we select different features for each two-class classifier. The true positive rate, false positive rate and discriminative index are taken to evaluate the performance of the classifier. Experimental results show that the classifier achieves good classification precision for the real and test data. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Ship detection and classification in high-resolution remote sensing imagery using shape-driven segmentation method

Ship detection and classification in high-resolution remote ...

引用

MIPPR 2009 - Automatic Target Recognition and Image Analysis: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Tao, Chao Tan, Yihua Cai, Huajie Tian, Jinwen State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Patter Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478061

High-resolution remote sensing imagery provides an important data source for ship detection and classification. However, due to shadow effect, noise and low-contrast between objects and background existing in this kind of data, traditional segmentation approaches have much difficulty in separating ship targets from complex sea-surface background. In this paper, we propose a novel coarse-to-fine segmentation strategy for identifying ships in 1-meter resolution imagery. This approach starts from a coarse segmentation by selecting local intensity variance as detection feature to segment ship objects from background. After roughly obtaining the regions containing ship candidates, a shape-driven level-set segmentation is used to extract precise boundary of each object which is good for the following stages such as detection and classification. Experimental results show that the proposed approach outperforms other algorithms in terms of recognition accuracy. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Ships

来源：评论

学校读者我要写书评

暂无评论

A new method of remote sensing image classification based on FSVM

A new method of remote sensing image classification based on...

引用

MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Cai, Huajie Tan, Yihua Tao, Chao Tian, Jinwen State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Patter Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

Since SVM is very sensitive to outliers and noises in the training set and the fuzzy feature exists in remote sensing images, we hereby studied fuzzy support vector machine based on the affinity among samples. The fuzzy membership is defined by not only the relation between a sample and its cluster center, but also the affinity among samples. A method defining the affinity among samples is proposed using a sphere with minimum volume while containing maximum of the samples. Then, the fuzzy membership is defined according to the position of samples in sphere space, which distinguished between the valid samples and the outliers or noises. The experiment results show, it discriminates support vectors with noise or outliers much better. Experimental results show that our method performs better than SVM in classification of the images in Wuhan and with less influnence by the noise interference. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

A flower algorithm for autonomous star identification in space surveillance

A flower algorithm for autonomous star identification in spa...

引用

MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Gong, Jiaqi Wu, Lin Gong, Junbin Ma, Jie Tian, Jinwen State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

The recent increase of space threats yields the idea of using the existing star trackers to perform surveillance of space objects from space. In the missions, due to the observer attitude dynamics, smearing affects the observed stars on the image in space surveillance. Besides, the reflecting flying space objects or debris as spurious stars affects the attitude determination. These are devastating for most star identification algorithms in star trackers. To resolve the problems, this paper defines a star pattern, called Flower code, which is composed of angular distances and circular angles as the characteristics of the pivot star. The angular distances are used for initial lookup table match. Moreover, the circular angles are used for the cyclic dynamic match between the sensor pattern and the pattern candidates from the initial match. The focus of the results is the evaluation of the influence of the reflecting flying spacecraft or debris as spurious stars and the attitude dynamics of the observer spacecraft, on the performance of the algorithms. A number of experiments are carried out on simulated images. The results demonstrated that the proposed method is efficient and robust. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Stars

来源：评论

学校读者我要写书评

暂无评论

A new circle targets extraction method from high resolution remote sensing imagery

A new circle targets extraction method from high resolution ...

引用

4th International Workshop on Advanced Computational Intelligence, IWACI 2011

作者： Chen, Z. Liu, J.G. Wang, G.Y. Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Multi-Spectral Information Processing State Key Laboratory China

ISBN: (纸本)9781612843735

According to the drawback of the traditional circle target extraction algorithm from high resolution remote sensing imagery used by Hough Transform, such as computation complexity, low efficiency and etc, a new circle target extraction method is proposed in this paper which can extract multiple circle targets with different radius at one time. First, the Average Absolute Difference is implemented to enhance the edge of the circle targets and suppress the noise of the background. Secondly, the locally self-adaptive segmentation algorithm is implemented to obtain the binary image. Thirdly, the thinning algorithm based on model computation is implanted to obtain the single pixel edge of the circle targets and in order to reduce the computation times in the following process. Furthermore, a pruning algorithm is necessary;finally, a modified Hough transform algorithm is proposed to obtain the circle targets. The experimental results demonstrate that the new circle targets algorithm can extract the multiple circle targets quickly and accurately, which has three advantages: low time consuming, high detection rate, robust to noise and fragmentary boundaries. © 2011 IEEE.

关键词： Binary images

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：