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P^2: a robust and rotationally invariant shape descriptor with applications to mesh saliency

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Applied Mathematics(A Journal of Chinese Universities) 2016年第1期31卷 53-67页

作者： LIU Xian-yong MA Li-zhuang LIU Li-gang School of Computer Science and Technology Shanghai Jiao Tong University

This work presents a robust and rotationally invariant shape descriptor, namely perception pronouncement （called p2）, to mathematically model the eye fixations, p2 takes two criteria - the local consideration of surface curvature and the global consideration of view- independent visibility - into account. Differing from existing works that often computed the intrinsic surface property of visibility in imaging space, a novel approach is proposed to approxi- mate the attribute in object space using Gauss map and Ray tracing. With the presented shape descriptor, mesh saliency detection, which refers to reasoning about which regions or points of a surface axe important, is more sensible, especially when 3D models fall into two categories：（1） the models possess significant interior/exterior structures; （2） the models contain regions where the contrast in visibility is high. For the models that are out of the categories, saliencies achieved by our approach are comparable to or even better than those of state-of-the-axt methods.

关键词： Human visual system mesh saliency shape descriptor bilateral filtering visibility.

Data driven composite shape descriptor design for shape retrieval with a VoR-Tree

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Applied Mathematics(A Journal of Chinese Universities) 2018年第1期33卷 88-106页

作者： WANG Zi-hao LIN Hong-wei XU Chen-kai School of Mathematical Science State Key Lab.of CAD&CG Zhejiang University

We develop a data driven method(probability model) to construct a composite shape descriptor by combining a pair of scale-based shape descriptors. The selection of a pair of scale-based shape descriptors is modeled as the computation of the union of two events, i.e.,retrieving similar shapes by using a single scale-based shape descriptor. The pair of scale-based shape descriptors with the highest probability forms the composite shape descriptor. Given a shape database, the composite shape descriptors for the shapes constitute a planar point set.A VoR-Tree of the planar point set is then used as an indexing structure for efficient query operation. Experiments and comparisons show the effectiveness and efficiency of the proposed composite shape descriptor.

关键词： shape descriptor shape retrieval shape analysis data-driven model

Local voxelizer:A shape descriptor for surface registration

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Computational Visual Media 2015年第4期1卷 279-289页

作者： Peng Song School of Computer Science and Technology University of Science and Technology of China

Surface registration brings multiple scans into a common coordinate system by aligning their overlapping components. This can be achieved by finding a few pairs of matched points on different scans using local shape descriptors and employing the matches to compute transformations to produce the alignment. By defining a unique local reference frame(LRF) and attaching an LRF to shape descriptors,the transformation can be computed using only one match based on aligning the LRFs. This paper proposes a local voxelizer descriptor,and the key ideas are to define a unique LRF using the support around a basis point,to perform voxelization for the local shape within a cubical volume aligned with the LRF,and to concatenate local features extracted from each voxel to construct the descriptor. An automatic rigid registration approach is given based on the local voxelizer and an expanding strategy that merges descriptor representations of aligned scans. Experiments show that our registration approach allows the acquisition of 3D models of various objects,and that the local voxelizer is robust to mesh noise and varying mesh resolution,in comparison to two state-of-the-art shape descriptors.

关键词： shape descriptor surface registration scan alignment 3D reconstruction

An anisotropic Chebyshev descriptor and its optimization for deformable shape correspondence

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Computational Visual Media 2023年第3期9卷 461-477页

作者： Shengjun Liu Hongyan Liu Wang Chen Dong-Ming Yan Ling Hu Xinru Liu Qinsong Li School of Mathematics and Statistics Central South UniversityChangsha 410000China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 101408China School of Mathematics and Statistics Hunan First Normal UniversityChangsha 410000China Big Data Institute Central South UniversityChangsha 410000China

shape descriptors have recently gained popularity in shape matching,statistical shape modeling,*** discriminative ability and efficiency play a decisive role in these *** this paper,we first propose a novel handcrafted anisotropic spectral descriptor using Chebyshev polynomials,called the anisotropic Chebyshev descriptor(ACD);it can effectively capture shape features in multiple *** ACD inherits many good characteristics of spectral descriptors,such as being intrinsic,robust to changes in surface discretization,***,due to the orthogonality of Chebyshev polynomials,the ACD is compact and can disambiguate intrinsic symmetry sinces everal directions are *** improve the ACD’s discrimination ability,we construct a Chebyshev spectral manifold convolutional neural network(CSMCNN)that optimizes the ACD and produces a learned *** experimental results show that the ACD outperforms existing state-of-the-art handcrafted *** combination of the ACD and the CSMCNN is better than other state-of-the-art learned descriptors in terms of discrimination,efficiency,and robustness to changes in shape resolution and discretization.

关键词： anisotropic descriptor spectral descriptor shape descriptor shape matching spectral convolution deep learning

Support Vector Machine active learning for 3D model retrieval

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2007年第12期8卷 1953-1961页

作者： LENG Biao QIN Zheng LI Li-qun Department of Computer Science and Technology Tsinghua University Beijing 100084 China School of Software Tsinghua University Beijing 100084 China

In this paper, we present a novel Support Vector Machine active learning algorithm for effective 3D model retrieval using the concept of relevance feedback. The proposed method learns from the most informative objects which are marked by the user, and then creates a boundary separating the relevant models from irrelevant ones. What it needs is only a small number of 3D models labelled by the user. It can grasp the user＇s semantic knowledge rapidly and accurately. Experimental results showed that the proposed algorithm significantly improves the retrieval effectiveness. Compared with four state-of-the-art query refinement schemes for 3D model retrieval, it provides superior retrieval performance after no more than two rounds of relevance feedback.

关键词： 3D model retrieval shape descriptor Relevance feedback Support Vector Machine (SVM) Active learning

Multi-sensor image registration using multi-resolution shape analysis

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2006年第4期7卷 549-555页

作者： YUAN Zhen-ming WU Fei ZHUANG Yue-ting School of Computer Science and Technology. Zhejiang University Hangzhou 310027 China School of Information Engineering Hangzhou Teacher＇s College Hangzhou 310036 China

Multi-sensor image registration has been widely used in remote sensing and medical image field, but registration performance is degenerated when heterogeneous images are involved. An image registration method based on multi-resolution shape analysis is proposed in this paper, to deal with the problem that the shape of similar objects is always invariant. The contours of shapes are first detected as visual features using an extended contour search algorithm in order to reduce effects of noise, and the multi-resolution shape descriptor is constructed through Fourier curvature representation of the contour’s chain code. Then a minimum distance function is used to judge the similarity between two contours. To avoid the effect of different resolution and intensity distribution, suitable resolution of each image is selected by maximizing the consistency of its pyramid shapes. Finally, the transformation parameters are estimated based on the matched control-point pairs which are the centers of gravity of the closed contours. Multi-sensor Landsat TM imagery and infrared imagery have been used as experimental data for comparison with the classical contour-based registration. Our results have been shown to be superior to the classical ones.

关键词： Image registration shape descriptor Feature matching Multi-resolution representation

Joint shape and color descriptors for 3D urban model retrieval

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International Journal of Digital Earth 2016年第11期9卷 1117-1134页

作者： Liang Zhang Liqiang Zhang Xiaojing Yao P.Takis Mathiopoulos Chunming Han State Key Laboratory of Remote Sensing Science Beijing Normal UniversityBeijingPeople’s Republic of China The Institute of Remote Sensing and Digital Earth Chinese Academy of SciencesBeijingPeople’s Republic of China Department of Informatics and Telecommunications University of AthensAthensGreece

With the rapid development of photogrammetry,computer vision and three-dimensional(3D)modeling technologies,it is possible to efficiently construct detailed 3D urban ***,large corpora of 3D models,such as the Google 3D Warehouse,are now becoming freely available on the *** to find the proper 3D urban models is a challenging research *** this paper,we join shape descriptors and color descriptors for 3D urban model *** query objects are localized and segmented automatically from the input images by using a new selective search voting *** combining the normalization with the light field descriptor,the Horizontal Light descriptor is introduced to measure the shape similarity among the normalized urban *** color descriptors are used to represent the color information of the urban *** two types of descriptors are joined to search 3D urban models similar to the query *** results have shown the effectiveness of our approach.

关键词： 3D urban models shape descriptor color descriptor model retrieval

Flame image recognition of alumina rotary kiln by artificial neural network and support vector machine methods

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Journal of Central South University of Technology 2008年第1期15卷 39-43页

作者：张红亮邹忠李劼陈湘涛 School of Metallurgical Science and Engineering Central South University School of Information Science and Engineering Central South University

Based on the Fourier transform, a new shape descriptor was proposed to represent the flame image. By employing the shape descriptor as the input, the flame image recognition was studied by the methods of the artificial neural network(ANN) and the support vector machine(SVM) respectively. And the recognition experiments were carried out by using flame image data sampled from an alumina rotary kiln to evaluate their effectiveness. The results show that the two recognition methods can achieve good results, which verify the effectiveness of the shape descriptor. The highest recognition rate is 88.83% for SVM and 87.38% for ANN, which means that the performance of the SVM is better than that of the ANN.

关键词： rotary kiln flame image image recognition shape descriptor artificial neural network support vector machine

Survey of lightweighting methods of huge 3D models for online Web3D visualization

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虚拟现实与智能硬件(中英文) 2023年第5期5卷 395-406页

作者： Xiaojun LIU Jinyuan JIA Chang LIU Department of mathematics and Information Engineering Nanhu College of Jiaxing UniversityZhejiang 314000China Department of Softwere Engineeging Tongji UniversityShanghai 201804China School of Information Technology Nanchang Hangkong UniversityNanchang 330063China

Background With the rapid development of Web3D technologies, the online Web3D visualization, particularly for complex models or scenes, has been in a great demand. Owing to the major conflict between the Web3D system load and resource consumption in the processing of these huge models, the huge 3D model lightweighting methods for online Web3D visualization are reviewed in this paper. Methods By observing the geometry redundancy introduced by man-made operations in the modeling procedure, several categories of light-weighting related work that aim at reducing the amount of data and resource consumption are elaborated for Web3D visualization. Results By comparing perspectives, the characteristics of each method are summarized, and among the reviewed methods, the geometric redundancy removal that achieves the lightweight goal by detecting and removing the repeated components is an appropriate method for current online Web3D visualization. Meanwhile, the learning algorithm, still in improvement period at present, is our expected future research topic. Conclusions Various aspects should be considered in an efficient lightweight method for online Web3D visualization, such as characteristics of original data, combination or extension of existing methods, scheduling strategy, cache man-agement, and rendering mechanism. Meanwhile, innovation methods, particularly the learning algorithm, are worth exploring.

关键词： Huge 3D model Lightweighting Web3D Visualization shape descriptor