Hasil untuk "Dancing"

Hameed Olutoba Lawal

Dance serves as a potent metaphor for Taiye Adeola’s Ni Ile Wa, embodying cultural identity, resistance, and transformation. This study explores the symbolic and narrative functions of dance within the text, and examines how movement and rhythm reflect societal tensions, personal struggles, and communal aspirations. Drawing on theories of performance, embodiment, and postcolonial aesthetics, this paper argues that dance in Ni Ile Wa is not merely an artistic expression, but a language through which characters negotiate power, memory, and belonging. Ultimately, work positions dance as a dynamic force that bridges the past and present, reinforcing cultural heritage while enabling new forms of self-expression.

Mariana Turner, Soledad Echegoyen

Los estudios de cinemática en la danza son un gran soporte para mejorar los movimientos. El objetivo del presente estudio fue identificar la manera de ejecución de la vuelta de pecho en el baile flamenco a través de un análisis cinemático de la inclinación del torso, la flexión de la rodilla y velocidad del giro. Se estudiaron a once bailaoras profesionales de flamenco (30 ± 3.6 años de edad). Cada una realizó tres vueltas consecutivas, a las que se les videograbó en tres planos: frontal, sagital y transversal desde una visión cenital. Se dividieron en dos grupos de acuerdo a la calidad de las vueltas. Se analizaron cinco fases del movimiento en los que se midió: tiempo de la fase, ángulo de flexión de la rodilla, flexión y extensión del torso y desplazamiento del centro de masa (CM) y de la cabeza. El tiempo para completar la vuelta fue de 1.3 ± 0.2 s. La inclinación del torso fue diferente en cada fase siendo en promedio 47.4º ± 14.4º, la flexión promedio de la rodilla de base 18.85º ± 7.3º. Los giros de mejor calidad tuvieron como característica mayor flexión de la rodilla (p<0.02) y mayor velocidad en la fase intermedia o extensión del torso (p<0.03). La flexión de la rodilla ayudó a mantener el CM dentro de la superficie de sustentación y lograr mejor equilibrio. Este es uno de los primeros estudios sobre cinemática de los giros en el baile flamenco, para entender la técnica, inclinación del torso y factores que influyen en la calidad. Se requieren de más estudios para mejorar la técnica y sobre todo la enseñanza de esta.

Seungho Eum, Ihjoon Cho, Junghyeon Kim

With the recent advancements in generative AI such as GAN, Diffusion, and VAE, the use of generative AI for dance generation has seen significant progress and received considerable interest. In this study, We propose R-Lodge, an enhanced version of Lodge. R-Lodge incorporates Recurrent Sequential Representation Learning named Dance Recalibration to original coarse-to-fine long dance generation model. R-Lodge utilizes Dance Recalibration method using $N$ Dance Recalibration Block to address the lack of consistency in the coarse dance representation of the Lodge model. By utilizing this method, each generated dance motion incorporates a bit of information from the previous dance motions. We evaluate R-Lodge on FineDance dataset and the results show that R-Lodge enhances the consistency of the whole generated dance motions.

Quang Nguyen, Nhat Le, Baoru Huang et al.

Estimating human dance motion is a challenging task with various industrial applications. Recently, many efforts have focused on predicting human dance motion using either egocentric video or music as input. However, the task of jointly estimating human motion from both egocentric video and music remains largely unexplored. In this paper, we aim to develop a new method that predicts human dance motion from both egocentric video and music. In practice, the egocentric view often obscures much of the body, making accurate full-pose estimation challenging. Additionally, incorporating music requires the generated head and body movements to align well with both visual and musical inputs. We first introduce EgoAIST++, a new large-scale dataset that combines both egocentric views and music with more than 36 hours of dancing motion. Drawing on the success of diffusion models and Mamba on modeling sequences, we develop an EgoMusic Motion Network with a core Skeleton Mamba that explicitly captures the skeleton structure of the human body. We illustrate that our approach is theoretically supportive. Intensive experiments show that our method clearly outperforms state-of-the-art approaches and generalizes effectively to real-world data.

Samuel Beck, Nina Doerr, Kuno Kurzhals et al.

Sports visualization has developed into an active research field over the last decades. Many approaches focus on analyzing movement data recorded from unstructured situations, such as soccer. For the analysis of choreographed activities like formation dancing, however, the goal differs, as dancers follow specific formations in coordinated movement trajectories. To date, little work exists on how visual analytics methods can support such choreographed performances. To fill this gap, we introduce a new visual approach for planning and assessing dance choreographies. In terms of planning choreographies, we contribute a web application with interactive authoring tools and views for the dancers' positions and orientations, movement trajectories, poses, dance floor utilization, and movement distances. For assessing dancers' real-world movement trajectories, extracted by manual bounding box annotations, we developed a timeline showing aggregated trajectory deviations and a dance floor view for detailed trajectory comparison. Our approach was developed and evaluated in collaboration with dance instructors, showing that introducing visual analytics into this domain promises improvements in training efficiency for the future.

Xuanchen Wang, Heng Wang, Dongnan Liu et al.

Generating dance from music is crucial for advancing automated choreography. Current methods typically produce skeleton keypoint sequences instead of dance videos and lack the capability to make specific individuals dance, which reduces their real-world applicability. These methods also require precise keypoint annotations, complicating data collection and limiting the use of self-collected video datasets. To overcome these challenges, we introduce a novel task: generating dance videos directly from images of individuals guided by music. This task enables the dance generation of specific individuals without requiring keypoint annotations, making it more versatile and applicable to various situations. Our solution, the Dance Any Beat Diffusion model (DabFusion), utilizes a reference image and a music piece to generate dance videos featuring various dance types and choreographies. The music is analyzed by our specially designed music encoder, which identifies essential features including dance style, movement, and rhythm. DabFusion excels in generating dance videos not only for individuals in the training dataset but also for any previously unseen person. This versatility stems from its approach of generating latent optical flow, which contains all necessary motion information to animate any person in the image. We evaluate DabFusion's performance using the AIST++ dataset, focusing on video quality, audio-video synchronization, and motion-music alignment. We propose a 2D Motion-Music Alignment Score (2D-MM Align), which builds on the Beat Alignment Score to more effectively evaluate motion-music alignment for this new task. Experiments show that our DabFusion establishes a solid baseline for this innovative task. Video results can be found on our project page: https://DabFusion.github.io.

E. V. Matyanova, E. Yu. Polishchuk, O. V. Kondrasheva et al.

A dance is considered from the perspective of art therapy, psychotherapy and kinesiotherapy as a component of therapeutic exercises. Previous experience with dance therapy in various rheumatic diseases is presented, and a theoretical rationale for adapting new dance styles for the purposes of complex non-drug treatment of rheumatologic patients is provided.

Аліна Миколаївна Підлипська, Лариса Юріївна Цвєткова

Мета статті – з’ясувати особливості опрацювання культурних травм у танцювальних практиках в історичній ретроспективі. Методологія. Застосовано хронологічний принцип, методи культурно-історичної реконструкції й мистецтвознавчого аналізу та ін. Наукова новизна. Представлене дослідження є однією з перших спроб введення танцювальних практик у предметне поле Trauma Studies в аспекті комплексного осмислення можливостей хореографічного мистецтва щодо опрацювання культурних травм та розробки стратегій детравматизації на різних історико-культурних етапах, включаючи й сьогодення в умовах російсько-української війни. Висновки. Одним із найкращих засобів опрацювання культурної травми на індивідуальному та колективному рівнях є танець, оскільки в хореографічному мистецтві травматична подія репрезентується й виражається мовою образів та опрацьовується через тіло з залученням складного комплексу тілесної пам’яті, тілесності як інтегративного феномену. Танець виконує не лише традиційні для мистецької та дозвіллєвої діяльності функції, а й у контексті подолання культурної травми актуалізує рекреаційні, релаксаційні, терапевтичні функції; важливо, що танець послаблює травматичний вплив на психоемоційну сферу людини. Опрацювання культурних травм Першої світової війни в дискурсі експресіонізму здійснює М. Вігман через звернення до тематики смерті, насильства, війни, самотності, страждань та ін. М. Грем опрацьовує травми індустріалізації, формування американської нації в зоні інтенсивної взаємодії різних культур, західної цивілізації як чоловічої, що породжує проблеми жіночої суб’єктності; одна з перших звертається до опрацювання колоніальної травми. З Другою світовою війною пов’язаний перехід танцю в терапевтичну модальність, виникнення танцювально-рухової терапії (М. Чейз та ін.). Танець Буто позиціонують як реакцію на травму, спричинену атомними бомбардуваннями Японії, а також як спосіб подолати проблеми кризи ідентичності. Сьогодні значних масштабів набуло опрацювання в танці травматичного досвіду російсько-української війни. Перспективними є дослідження, пов’язані з опрацюванням в танцювальних практиках досвіду українців, набутого в часи перебування українських земель у складі Російської імперії та СРСР, Голодомору, російсько-української війни, а також Голокосту, що був величезним викликом для цивілізації, а не локальним конфліктом.

Matthew Peters, McKenzie Schweitzer, A. Jamil Tajik

Abstract We present a case of a ruptured mitral valve chorda visualized using the high temporal and axial resolution of transthoracic M‐mode echocardiography.

David S. Hardin

Dancing Links connotes an optimization to a circular doubly-linked list data structure implementation which provides for fast list element removal and restoration. The Dancing Links optimization is used primarily in fast algorithms to find exact covers, and has been popularized by Knuth in Volume 4B of his seminal series The Art of Computer Programming. We describe an implementation of the Dancing Links optimization in the Rust programming language, as well as its formal verification using the ACL2 theorem prover. Rust has garnered significant endorsement in the past few years as a modern, memory-safe successor to C/C++ at companies such as Amazon, Google, and Microsoft, and is being integrated into both the Linux and Windows operating system kernels. Our interest in Rust stems from its potential as a hardware/software co-assurance language, with application to critical systems. We have crafted a Rust subset, inspired by Russinoff's Restricted Algorithmic C (RAC), which we have imaginatively named Restricted Algorithmic Rust, or RAR. In previous work, we described our initial implementation of a RAR toolchain, wherein we simply transpile the RAR source into RAC. By so doing, we leverage a number of existing hardware/software co-assurance tools with a minimum investment of time and effort. In this paper, we describe the RAR Rust subset, describe our improved prototype RAR toolchain, and detail the design and verification of a circular doubly-linked list data structure employing the Dancing Links optimization in RAR, with full proofs of functional correctness accomplished using the ACL2 theorem prover.

Alexei A. Deriglazov

Equations of a rotating body with one point constrained to move freely on a plane (dancing top) are deduced from the Lagrangian variational problem. They formally look like the Euler-Poisson equations of a heavy body with fixed point, immersed in a fictitious gravity field. Using this analogy, we have found examples of analytical solutions for the case of a heavy symmetrical dancing top. They describe the motions with center of mass keeping its height fixed above the supporting plane. General solution to equations of a dancing top in terms of exponential of Hamiltonian field is given. An extra constraint, that take into account the reaction of supporting plane, leads to modification of the canonical Poisson structure and therefore the integrability according to Liouville is under the question.

Zhongyang Zhang, Kaidong Chai, Haowen Yu et al.

As a beloved sport worldwide, dancing is getting integrated into traditional and virtual reality-based gaming platforms nowadays. It opens up new opportunities in the technology-mediated dancing space. These platforms primarily rely on passive and continuous human pose estimation as an input capture mechanism. Existing solutions are mainly based on RGB or RGB-Depth cameras for dance games. The former suffers in low-lighting conditions due to the motion blur and low sensitivity, while the latter is too power-hungry, has a low frame rate, and has limited working distance. With ultra-low latency, energy efficiency, and wide dynamic range characteristics, the event camera is a promising solution to overcome these shortcomings. We propose YeLan, an event camera-based 3-dimensional high-frequency human pose estimation(HPE) system that survives low-lighting conditions and dynamic backgrounds. We collected the world's first event camera dance dataset and developed a fully customizable motion-to-event physics-aware simulator. YeLan outperforms the baseline models in these challenging conditions and demonstrated robustness against different types of clothing, background motion, viewing angle, occlusion, and lighting fluctuations.

Siqi Yang, Zejun Yang, Zhisheng Wang

Dancing with music is always an essential human art form to express emotion. Due to the high temporal-spacial complexity, long-term 3D realist dance generation synchronized with music is challenging. Existing methods suffer from the freezing problem when generating long-term dances due to error accumulation and training-inference discrepancy. To address this, we design a conditional diffusion model, LongDanceDiff, for this sequence-to-sequence long-term dance generation, addressing the challenges of temporal coherency and spatial constraint. LongDanceDiff contains a transformer-based diffusion model, where the input is a concatenation of music, past motions, and noised future motions. This partial noising strategy leverages the full-attention mechanism and learns the dependencies among music and past motions. To enhance the diversity of generated dance motions and mitigate the freezing problem, we introduce a mutual information minimization objective that regularizes the dependency between past and future motions. We also address common visual quality issues in dance generation, such as foot sliding and unsmooth motion, by incorporating spatial constraints through a Global-Trajectory Modulation (GTM) layer and motion perceptual losses, thereby improving the smoothness and naturalness of motion generation. Extensive experiments demonstrate a significant improvement in our approach over the existing state-of-the-art methods. We plan to release our codes and models soon.

Xin Gao, Li Hu, Peng Zhang et al.

In the realm of 3D digital human applications, music-to-dance presents a challenging task. Given the one-to-many relationship between music and dance, previous methods have been limited in their approach, relying solely on matching and generating corresponding dance movements based on music rhythm. In the professional field of choreography, a dance phrase consists of several dance poses and dance movements. Dance poses composed of a series of basic meaningful body postures, while dance movements can reflect dynamic changes such as the rhythm, melody, and style of dance. Taking inspiration from these concepts, we introduce an innovative dance generation pipeline called DanceMeld, which comprising two stages, i.e., the dance decouple stage and the dance generation stage. In the decouple stage, a hierarchical VQ-VAE is used to disentangle dance poses and dance movements in different feature space levels, where the bottom code represents dance poses, and the top code represents dance movements. In the generation stage, we utilize a diffusion model as a prior to model the distribution and generate latent codes conditioned on music features. We have experimentally demonstrated the representational capabilities of top code and bottom code, enabling the explicit decoupling expression of dance poses and dance movements. This disentanglement not only provides control over motion details, styles, and rhythm but also facilitates applications such as dance style transfer and dance unit editing. Our approach has undergone qualitative and quantitative experiments on the AIST++ dataset, demonstrating its superiority over other methods.

Wenjie Yin, Qingyuan Yao, Yi Yu et al.

Lyrics often convey information about the songs that are beyond the auditory dimension, enriching the semantic meaning of movements and musical themes. Such insights are important in the dance choreography domain. However, most existing dance synthesis methods mainly focus on music-to-dance generation, without considering the semantic information. To complement it, we introduce JustLMD, a new multimodal dataset of 3D dance motion with music and lyrics. To the best of our knowledge, this is the first dataset with triplet information including dance motion, music, and lyrics. Additionally, we showcase a cross-modal diffusion-based network designed to generate 3D dance motion conditioned on music and lyrics. The proposed JustLMD dataset encompasses 4.6 hours of 3D dance motion in 1867 sequences, accompanied by musical tracks and their corresponding English lyrics.

Jiashuo Yu, Junfu Pu, Ying Cheng et al.

Although audio-visual representation has been proved to be applicable in many downstream tasks, the representation of dancing videos, which is more specific and always accompanied by music with complex auditory contents, remains challenging and uninvestigated. Considering the intrinsic alignment between the cadent movement of dancer and music rhythm, we introduce MuDaR, a novel Music-Dance Representation learning framework to perform the synchronization of music and dance rhythms both in explicit and implicit ways. Specifically, we derive the dance rhythms based on visual appearance and motion cues inspired by the music rhythm analysis. Then the visual rhythms are temporally aligned with the music counterparts, which are extracted by the amplitude of sound intensity. Meanwhile, we exploit the implicit coherence of rhythms implied in audio and visual streams by contrastive learning. The model learns the joint embedding by predicting the temporal consistency between audio-visual pairs. The music-dance representation, together with the capability of detecting audio and visual rhythms, can further be applied to three downstream tasks: (a) dance classification, (b) music-dance retrieval, and (c) music-dance retargeting. Extensive experiments demonstrate that our proposed framework outperforms other self-supervised methods by a large margin.

Peyton N. Carter, Peyton N. Carter, Eric E. Hall et al.

Social media platforms are an accessible and increasingly used way for the public to gather healthcare-related information, including on sports injuries. “TikTok” is currently one of the fastest-growing social media platforms worldwide, and it is especially popular amongst adolescents and young adults. The widespread use and popularity of TikTok suggests that this platform has potential to be a source for healthcare information for younger individuals. The aim of this study was to gain a preliminary understanding of the concussion/head injury-related information on TikTok, and to gauge if TikTok could serve as a platform for concussion education. This exploratory study used a systematic search strategy to understand more about how concussion is being portrayed through TikTok videos. Using the keywords “concussion” and “head injury,” 200 videos were downloaded from TikTok and 43 videos were excluded. Of the 92 videos retrieved using the keyword “concussion,” 95% (n = 88) had more than 100,000 views and 6% (n = 10) had been viewed more than 10 million times. Over half, 54% (n = 50) of the “concussion” videos depicted individuals “playing around” and getting hit in the head, whilst only 1% (n = 1) of the TikTok videos were categorized as “explaining concussion facts.” The large numbers of views of concussion-related TikTok videos demonstrates the popularity of this platform and indicates that healthcare organizations should consider TikTok as a potential means for concussion education amongst younger individuals.

Permata Widianingrum, Agung Budi Sardjono

New tourism in Semarang City raises a problem, traffic congestion. New tourism provided in Semarang City by utilizing the existing potensial is Semarang Bridge Fountain. Semarang Bridge Fountain is a dancing fountain located in Semarang City, which inaugurated end of 2018. Located on the West Canal Flood River and becomes new icon in Semarang City. The existence of Semarang Bridge Fountain affects the surrounding road infrastructure. Namely the emergence of traffic jams when the fountain attraction takes place caused by many vehicles parked on Jenderal Sudirman street. The purpose of this research to analyze road infrastructure can be used as parking lots. The method used in this research is descriptive qualitative to explain state of West Canal Flood River. The results of this research shows that parking area became one of problems that arise during event. Many people don’t know location of official parking area provided by City Government. Congestion arises because the community gathers at one point during the event and also does not know the official parking location. From the results of analysis can be concluded need for delivery of official parking location information for community, need for firmness of official parties related arrangement of parking, also the addition of facilities so that activities aren’t concentrated at one point.

Vanessa Benites Bordin

Experienciar um ritual pertencente a outra cultura proporciona pensarmos questões relacionadas à nossa própria cultura, a partir de uma espécie de ‘distanciamento’, pois ao ‘olhar’ o outro percebemos aspectos de nós mesmos. Para uma performer, vivenciar um ritual de iniciação feminina, no caso aqui, do povo indígena Tikuna: Worecü, é refletir sobre o quanto o contexto em que vivemos influência nosso fazer artístico, já que vida e arte estão entrelaçadas, pensando a partir do conceito de artivismo.

Sarah Pini, Kate Maguire-Rosier