Localized LRR on Grassmann Manifold: An Extrinsic View

Wang, Boyue; Hu, Yongli; Gao, Junbin; Sun, Yanfeng; Yin, Baocai

doi:10.1109/tcsvt.2017.2757063

Cited by 16 publications

(6 citation statements)

References 69 publications

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“…This paper discusses the possibility of extending the subspace data LRR on manifolds. Instead of embedding manifolds directly in symmetric matrix space, it establishes a local self-representation in the tangent space of each point, so as to obtain the local LRR method of manifolds, but there is still a lack of detailed explanation steps [1]. Taktaktak Kal-lel believes that the study compares the effects of positive feedback and negative feedback on students' dance learning.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Role of Ballet Basic Skills Training Based on Multimedia Video in International Standard Dance Teaching

Wang

Seo

2021

Journal of Sensors

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Ballet and sports dance are also dance art from the west, which are popular among the Chinese people after they were introduced into China. With the popularization of compulsory education, people now like to let children learn all kinds of art skills. For instance, dance is very popular with parents, and then to the common development and promotion of career, we also realize that the development of online dance education and dance is more and more extensive pan. Through the introduction of ballet research, this paper explores the application of multimedia-based ballet basic skills training in international standard dance teaching. The research results can make dancers, especially beginners, truly understand the training value of ballet basic skills training and pay enough attention to this course. This paper uses the ways of literature analysis, experimental investigation, and multimedia ballet teaching text experiment to study the application of ballet in modern international standard dance teaching. It reflects the number of people learning ballet and learning motivation. Based on the extensive application of multimedia ballet basic skills training in international standard dance teaching, we can really understand the significance of ballet basic training for the whole dance teaching the value of learning. The experimental results show that 70% of ballet scholars believe that the basic skills training of ballet has a very high requirement on the body, and the motivation of learning ballet is also different. Dancers use the theoretical knowledge of dance science teaching and ballet basic training to make an overall connection, and multimedia video ballet basic skills training exercises the foundation in dance. It also plays an important role in the teaching of international standard dance.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Role of Ballet Basic Skills Training Based on Multimedia Video in International Standard Dance Teaching

Wang

Seo

2021

Journal of Sensors

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“…Table 5 summarized the performance of the proposed framework for Ballet dataset. Moreover, the comparison with the recent state-of-the-arts (Liu & Pei, 2014;Ming et al, 2014;Vishwakarma et al, 2016a;Wang, Hu, et al, 2017;Zhu & Xia, 2015) in also surpasess all the existing state-of-the-arts which utilized SDEG and R-Transform-based action descriptor (Vishwakarma et al, 2016), optical flow features (Liu & Pei, 2014;Zhu & Xia, 2015) to assimilate shape and temporal variation of action with SVM classifier. It is also identified that the concept of Multiple Instance Learning using Iterative Querying Heuristic algorithm (Zhu & Xia, 2015) instead of SVM resulted in better results…”

Section: Performance Comparison With State-of-the-artmentioning

confidence: 68%

A sparse coded composite descriptor for human activity recognition

et al. 2021

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This paper proposes a novel algorithm for computing discriminative descriptors named as a sparse coded composite descriptor (SCCD) for robust human activity recognition. The proposed method blends the state-of-the-art handcrafted features and the discriminative nature of the sparse representation of visual information. The human activity is firstly modelled using any handcrafted feature, and then the sparse codes computed on a discriminative sparse dictionary of these features are embedded to provide discrimination in the feature set. Finally, a support vector machine (SVM) is trained using the proposed SCCDs to perform classification of different human activities. A new feature named as differential motion descriptor (DMD) is also proposed to extract the motion as well as spatial information from an activity video. The simulation results reveal that in comparison with the handcrafted feature, the corresponding SCCD improves the recognition accuracy significantly. The proposed method is compared with state-of-the-art methods on KTH, Ballet, UCF50, and HMDB51 datasets and the proposed methodology of composite features outperforms these methods in terms of recognition accuracy.

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“…Low-rank representation (LRR) has recently attracted considerable interest as its pleasing efficacy in exploring low-dimensional subspace structures embedded in data, which is very helpful for data clustering. However, in many computer vision applications, data often originate from a manifold, which is equipped with some Riemannian geometry, and the low-rank representation over the manifold [14,42,45] is required. This problem can be formulated as min…”

Section: Low-rank Representation Over the Manifoldmentioning

confidence: 99%

Normal Cones Intersection Rule and Optimality Analysis for Low-Rank Matrix Optimization with Affine Manifolds

Li¹,

Luo²

2022

Preprint

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The low-rank matrix optimization with affine manifold (rank-MOA) aims to minimize a continuously differentiable function over a low-rank set intersecting with an affine manifold. This paper is devoted to the optimality analysis for rank-MOA. As a cornerstone, the intersection rule of the Fréchet normal cone to the feasible set of the rank-MOA is established under some mild linear independence assumptions. Aided with the resulting explicit formulae of the underlying normal cone, the so-called F -stationary point and the α-stationary point of rank-MOA are investigated and the relationship with local/global minimizers are then revealed in terms of first-order optimality conditions. Furthermore, the second-order optimality analysis, including the necessary and the sufficient conditions, is proposed based on the second-order differentiation information of the model. All these results will enrich the theory of low-rank matrix optimization and give potential clues to designing efficient numerical algorithms for seeking low rank solutions. Meanwhile, two specific applications of the rank-MOA are discussed to illustrate our proposed optimality analysis.

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Localized LRR on Grassmann Manifold: An Extrinsic View

Cited by 16 publications

References 69 publications

[Retracted] Role of Ballet Basic Skills Training Based on Multimedia Video in International Standard Dance Teaching

[Retracted] Role of Ballet Basic Skills Training Based on Multimedia Video in International Standard Dance Teaching

A sparse coded composite descriptor for human activity recognition

Normal Cones Intersection Rule and Optimality Analysis for Low-Rank Matrix Optimization with Affine Manifolds

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