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Dual Branch PnP Based Network for Monocular 6D Pose Estimation

Intelligent Automation & Soft Computing 2023年第6期36卷 3243-3256页

作者： Jia-Yu Liang Hong-Bo Zhang Qing Lei Ji-Xiang Du Tian-Liang Lin Department of Computer Science and Technology Huaqiao UniversityXiamen361000China Xiamen Key Laboratory of Computer Vision and Pattern Recognition Huaqiao UniversityXiamen361000China Fujian Key Laboratory of Big Data Intelligence and Security Huaqiao UniversityXiamen361000China College of Mechanical Engineering and Automation Xiamen361000China

Monocular 6D pose estimation is a functional task in the field of com-puter vision and *** recent years,2D-3D correspondence-based methods have achieved improved performance in multiview and depth data-based ***,for monocular 6D pose estimation,these methods are affected by the prediction results of the 2D-3D correspondences and the robustness of the per-spective-n-point(PnP)*** is still a difference in the distance from the expected estimation *** obtain a more effective feature representation result,edge enhancement is proposed to increase the shape information of the object by analyzing the influence of inaccurate 2D-3D matching on 6D pose regression and comparing the effectiveness of the intermediate ***,although the transformation matrix is composed of rotation and translation matrices from 3D model points to 2D pixel points,the two variables are essentially different and the same network cannot be used for both variables in the regression ***,to improve the effectiveness of the PnP algo-rithm,this paper designs a dual-branch PnP network to predict rotation and trans-lation ***,the proposed method is verified on the public LM,LM-O and YCB-Video *** ADD(S)values of the proposed method are 94.2 and 62.84 on the LM and LM-O datasets,*** AUC of ADD(-S)value on YCB-Video is *** experimental results show that the performance of the proposed method is superior to that of similar methods.

关键词： 6D pose monocular RGB edge enhancement dual-branch PnP 2D-3D correspondence

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An improved K-OPT local search algorithm for the vertex separator problem

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Journal of Computational and Theoretical Nanoscience 2015年第11期12卷 4942-4958页

作者： Zhang, Zhiqiang Shao, Zehui Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province China School of Computer Science Chengdu University Chengdu610106 China

A vertex separator in an undirected graph is a subset of the vertices, whose removal disconnects the graph in at least two nonempty connected components. Given a connected undirected graph G = (V ,E) with |V| = n, an integer 1 ≤ b ≤ n, the vertex separator problem (VSP) asks to find a partition of V into disjoint sets A, B, C, with A and B nonempty, such that (1) E contains no edge (i, j) with i A, j ? B, (2) max{|A|} |B|} = b, (3) |C| is minimized. The vertex separator problem is a classic NP complete problem. It is widely applied to circuit design, computer network communication, protein combination in bioinformatics, etc. At present there has already been exact algorithm to search vertex separator of undirected graph, while there are only few heuristic algorithms. Aiming at the VSP and a solution design for heuristic algorithm, this paper designs an improved K-OPT local search algorithm. In order to compare the searching efficiency of a variety of heuristic algorithms for VSP, this paper also designs simulated annealing algorithm and variable neighborhood search algorithm, and performs comparative experiments on these algorithms using DIMACS graph, MATRIXMARKET graph, MIPLIB graph. The experimental results show that the improved K-OPT local search algorithm goes the best. In the experiment, using improved K-OPT local search algorithm, existing Relax-and-Cut algorithm is further compared, whose experimental results show that in some graph tests, the improved K-OPT local search algorithm goes better than Relax-and-Cut algorithm. © 2015 American Scientific Publishers.

关键词： Undirected graphs

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Wavelength dependent loss of splice of single-mode fibers

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Journal of Central South University 2013年第7期20卷 1832-1837页

作者： YANG Bo DUAN Ji-an XIE Zheng XIAO Hong-feng State Key Laboratory of High Performance Complex Manufactory (Central South University) Changsha 410083 China Institution of Image Recognition and Computer Vision Hunan Normal University Changsha 410081 China

After reviewing three different definitions of mode field diameter of single-mode fibers, coupled efficiency calculation methods associated with lateral offset, longitude separation and wavelength, the effects produced by them, and the influences of splicing defects were discussed in detail. The regularities of the effects were studied according to the first order derivation of couple efficiency formula, and a simplified formula for couple efficiency calculation was presented under the circumstance of slight misalignment, with respect to wavelength, 2, and in a good agreement with the theoretical model. The simplified formula provides a new but simple approach to evaluate wavelength dependent couple efficiency of single-mode fibers. Theoretical analyses and numerical calculations show that, when those defects exist, the wavelength produces additional effects on the couple loss that growth of wavelength causes an increase on the couple efficiency for the lateral offset or longitude separation whereas lessens the couple efficiency due to angular misalignment or mode fields mismatching, and that the wavelength degrades the couple efficiency distinctly when λ≥2.5 μm whereas it distorts the couple slightly in range of λ≤2λ≤2 μm.

关键词： wavelength dependent loss couple efficiency single-mode fiber cut-offwavelength

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PON: Proposal Optimization Network for Temporal Action Proposal Generation 16th

PON: Proposal Optimization Network for Temporal Action Propo...

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16th International Conference on Intelligent Computing, ICIC 2020

作者： Peng, Xiaoxiao Du, Jixiang Zhang, Hongbo Department of Computer Science and Technology Huaqiao University Quanzhou China Fujian Key Laboratory of Big Data Intelligence and Security Huaqiao University Quanzhou China Xiamen Key Laboratory of Computer Vision and Pattern Recognition Huaqiao University Quanzhou China

ISBN: (纸本)9783030607951

Temporal action localization is a challenging task in video understanding. Although great progress has been made in temporal action localization, the most advanced methods still have the problem of sharp performance degradation when an action proposal generated. Most methods use sliding windows method or simply group frames according to frame-level scores. These methods are not enough to provide accurate action boundary and maintain reasonable temporal structure. In order to solve these problems, we propose a novel proposal optimization network to generate start score, end score, action score and regression score, and then remove the redundancy by NMS algorithm. In the proposed method, we introduce a metric loss function to maintain the temporal structure of action proposal in the training process. To verify the effectiveness of the proposed method, we have made comparative experiments on ActivityNet-1.3 dataset respectively, and the proposed method has surpassed some of the state-of-the-art methods on the dataset. © 2020, Springer Nature Switzerland AG.

关键词： Passive optical networks

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Warp that smile on your face: Optimal and smooth deformations for face recognition

Warp that smile on your face: Optimal and smooth deformation...

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作者： Gass, Tobias Pishchulin, Leonid Dreuw, Philippe Ney, Hermann Computer Vision Laboratory ETH Zurich Switzerland Computer Vision and Multimodal Computing MPI Informatics Saarbruecken Germany Human Language Technology and Pattern Recognition Group RWTH Aachen University Germany

ISBN: (纸本)9781424491407

In this work, we present novel warping algorithms for full 2D pixel-grid deformations for face recognition. Due to high variation in face appearance, face recognition is considered a very difficult task, especially if only a single reference image, for example a mug-shot, per face is available. Usually model-based approaches with additional training data are used to cope with several types of variation occurring in facial imaging. Image warping contrarily yields a distance measure which is invariant with regard to several types of variation. This allows for precise recognition even using only very few reference observations. Due to the computationally complex problem of optimal 2D warping, pseudo-2D warping-based approaches in the past represented strong approximations of the original problem, and were mainly successful on data with low variability or rectified images. We propose a novel 2D warping method which is globally optimal and makes no prior assumtions on the data variability besides two-dimensional smootheness constraints which both avoid local mirroring and gaps and significantly speed up the optimization. Furthermore, we show that occlusion handling is imperative to obtain smooth warpings in a variety of domains. We evaluate our novel algorithm on various well known databases, such as the AR-Face and CMU-PIE database, and provide a detailed comparison to existing warping approaches. We show that by using simple relative 2D constraints, strong local features and a kernel, which is robust w.r.t. occlusions, our computationally complex approaches outperform state-of-the-art results for recognizing faces under varying expressions, occlusions and poses. Most interestingly, we achieve higher accuracy using fewer training instances per class compared to methods learning a model of the 3D shape. © 2011 IEEE.

关键词： Face recognition

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Temporal conditional random fields: A conditional state space predictor for visual tracking

Temporal conditional random fields: A conditional state spac...

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Iranian Conference on Machine vision and Image Processing

作者： Shafiee, M.J. Azimifar, Z. Fieguth, P. Computer Vision and Pattern Recognition Laboratory School of Electrical and Computer Engineering Shiraz University Shiraz Iran Systems Design Engineering University of Waterloo Waterloo ON Canada

ISBN: (纸本)9781424497065

We present a modified Temporal Conditional Random Fields framework for modeling and predicting object motion. To facilitate such a powerful graphical model with prediction and come up with a CRF-based predictor, we propose a set of new temporal relations for object tracking, with feature functions such as optical flow (calculated among consequent frames). We evaluate our proposed Temporal Conditional Random Field method with real and synthetic data sequences and will show that the TCRF prediction is nearly equivalent with result of template matching. Experimental results show that our proposed method estimates future target state with zero error until target dynamic changes. Our proposed modified CRF method with simple and easy to implement feature functions, can learn any target dynamic, thus, it can predict next state of target with zero error. © 2010 IEEE.

关键词： Template matching

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Spatio-temporal Attention Graph Convolutions for Skeleton-based Action recognition 23rd

Spatio-temporal Attention Graph Convolutions for Skeleton-b...

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22nd Scandinavian Conference on Image Analysis, SCIA 2023

作者： Le, Cuong Liu, Xin Computer Vision and Pattern Recognition Laboratory School of Engineering Science Lappeenranta-Lahti University of Technology LUT Lappeenranta Finland Computer Vision Laboratory Department of Electrical Engineering Linköping University Linköping Sweden

ISBN: (纸本)9783031314346

In skeleton-based action recognition, graph convolutional networks (GCN) have been applied to extract features based on the dynamic of the human body and the method has achieved excellent results recently. However, GCN-based techniques only focus on the spatial correlations between human joints and often overlook the temporal relationships. In an action sequence, the consecutive frames in a neighborhood contain similar poses and using only temporal convolutions for extracting local features limits the flow of useful information into the calculations. In many cases, the discriminative features can present in long-range time steps and it is important to also consider them in the calculations to create stronger representations. We propose an attentional graph convolutional network, which adapts self-attention mechanisms to respectively model the correlations between human joints and between every time steps for skeleton-based action recognition. On two common datasets, the NTU-RGB+D60 and the NTU-RGB+D120, the proposed method achieved competitive classification results compared to state-of-the-art methods. The project’s GitHub page: STA-GCN. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Convolution

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Using electromagnetic input for multi-user or two-handed spatial gestural interaction based on the digital compass 15

Using electromagnetic input for multi-user or two-handed spa...

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17th International Conference on Human-computer Interaction with Mobile Devices and Services, MobileHCI 2015

作者： Yuksel, Kamer Ali Baz, Ipek Ozduman, Haluk Computer Vision and Pattern Recognition Laboratory Sabanci University Turkey Research Center for ICT German Turkish Advanced Technical University of Berlin Germany

ISBN: (纸本)9781450336529

Multiple researchers recently proposed the use of the digital compass embedded in mobile devices for touchless interaction in the 3D space around them. These methods overcome several limits imposed by other interaction techniques and were evaluated for a variety of uses. However, they do not support collaborative settings and are prone to dynamic noise caused by external conditions, as with most other sensor-based interaction techniques. In this paper, we propose the use of frequency-modulated electromagnets as an input medium for magnetic interaction to overcome its various constraints and further enable multi-user and two-handed input. Furthermore, we demonstrated the hardware design specifications of a novel input device, referred to as electromagnetic stylus, which is prototyped to conduct a user-study on the proposed method. Experimental results indicate that gestures performed simultaneously by four electromagnetic styli can accurately be recognized using a single magnetic field sensor, and dynamic noises can be substantially reduced. © 2015 ACM.

关键词： Timing circuits

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Plankton recognition in Images with Varying Size 25th

Plankton Recognition in Images with Varying Size

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25th International Conference on pattern recognition Workshops, ICPR 2020

作者： Bureš, Jaroslav Eerola, Tuomas Lensu, Lasse Kälviäinen, Heikki Zemčík, Pavel Computer Vision and Pattern Recognition Laboratory LUT University Lappeenranta Finland Faculty of Information Technology Brno University of Technology Brno Czech Republic

ISBN: (纸本)9783030687793

Monitoring plankton is important as they are an essential part of the aquatic food web as well as producers of oxygen. Modern imaging devices produce a massive amount of plankton image data which calls for automatic solutions. These images are characterized by a very large variation in both the size and the aspect ratio. Convolutional neural network (CNN) based classification methods, on the other hand, typically require a fixed size input. Simple scaling of the images into a common size contains several drawbacks. First, the information about the size of the plankton is lost. For human experts, the size information is one of the most important cues for identifying the species. Second, downscaling the images leads to the loss of fine details such as flagella essential for species recognition. Third, upscaling the images increases the size of the network. In this work, extensive experiments on various approaches to address the varying image dimensions are carried out on a challenging phytoplankton image dataset. A novel combination of methods is proposed, showing improvement over the baseline CNN. © 2021, Springer Nature Switzerland AG.

关键词： Aspect ratio

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Mem Brain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction

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Nano-Micro Letters 2018年第1期10卷 12-19页

作者： Xi Yin Jing Yang Feng Xiao Yang Yang Hong-Bin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Computer Science Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering

Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels,transporters, receptors. Because it is difficult to determinate the membrane protein's structure by wet-lab experiments,accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called Mem Brain, whose input is the amino acid sequence. Mem Brain consists of specialized modules for predicting transmembrane helices, residue–residue contacts and relative accessible surface area of a-helical membrane proteins. Mem Brain achieves aprediction accuracy of 97.9% of ATMH, 87.1% of AP,3.2 ± 3.0 of N-score, 3.1 ± 2.8 of C-score. Mem BrainContact obtains 62%/64.1% prediction accuracy on training and independent dataset on top L/5 contact prediction,respectively. And Mem Brain-Rasa achieves Pearson correlation coefficient of 0.733 and its mean absolute error of13.593. These prediction results provide valuable hints for revealing the structure and function of membrane *** Brain web server is free for academic use and available at ***/bioinf/Mem Brain/.

关键词： Transmembrane a-helices Structure prediction Machine learning Contact map prediction Relative accessible surface area

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