Sangeeta Jadhav

Bio: Sangeeta Jadhav is an academic researcher from Cork College of Commerce. The author has contributed to research in topics: Dance & Choreography. The author has an hindex of 5, co-authored 9 publications receiving 45 citations. Previous affiliations of Sangeeta Jadhav include Goa University.

Art to SMart: An evolutionary computational model for BharataNatyam choreography

Abstract: Dance choreography is an intense, creative and intuitive process. A choreographer has to finalize appropriate dance steps from amongst millions of possibilities. Though it is not impossible, the choreographer being human cannot explore, analyze and remember all these variations among steps due to large scale of available options. Hence, we propose to simplify the problem of exploring and selecting dance steps from amongst the huge set of all possible variations for an Indian Classical Dance, BharataNatyam (BN). Based on a computational model developed by Jadhav et al. [13], we propose a Genetic Algorithm (GA) driven automatic system that would provide a list of unexplored novel dance steps to choreographers. We have incorporated certain measures to ensure that the proposed dance steps should be feasible and appropriate. In this paper, we discuss an automated approach to obtain unexplored dance steps using a proposed fitness function for a single beat/count. The details of experimental study performed for the Genetic Algorithm based art to SMart (System Modelled art) system along with the results obtained are also presented in this paper.

Modeling BharataNatyam dance steps: art to SMart

Abstract: BharataNatyam (BN) like any other Indian classical dance comprises of a sequence of possible and legitimate dance steps. It is estimated that using the main body parts namely head, neck, hand and leg itself, more than 5 lakh dance steps can be generated for a single beat. Choreographers and even dancers usually repeat their favorite dance steps or the conventional casual dance steps taught by their teacher while performing for multiple beats. As a result several valid and many other significant non-traditional dance steps remain unexplored. Hence, we propose to have an auto enumeration followed by auto classification of significant BN dance steps that can be used in dance performance and choreography. In short, we try to transform sheer art into a System Modelled art i.e. 'Art to SMart'. The foremost and most challenging task is to have a computational model that represents different BN dance poses. In this paper, we have proposed a computational model to represent BN dance steps and have presented the detailed description of formulation of a dance position vector that comprises of thirty explicitly identified attributes to capture and represent all variations of a BN dance step. We have named it as a SMart system for modelling BN steps, where SMart stands for System Modelled art. We have also demonstrated sample dance steps and their corresponding representations with appropriate dance step images.

Art to SMart: An Automated BharataNatyam Dance Choreography

Abstract: Hence, we propose to develop an autoenumeration followed by autoclassification of significant BN dance steps that can be used in dance performance and choreography. The foremost and most challenging task is to have a computational model that represents different BN dance poses. The second task is to develop a genetic algorithm GA-driven automatic system that would provide choreographers a list of unexplored, novel dance steps to fit in a single beat. We designed Art to SMart as a system to model the dance art of BharataNatyam. This system generates dance poses. Furthermore, we have developed a stick figure generation module to help visualize the 30-attribute dance vector generated from the system. The results are evaluated using a mean opinion score measure.

An Extensive Review of Computational Dance Automation Techniques and Applications

Abstract: Dance is an art and when technology meets this kind of art, it's a novel attempt in itself. Several researchers have attempted to automate several aspects of dance, right from dance notation to choreography. Furthermore, we have encountered several applications of dance automation like e-learning, heritage preservation, etc. Despite several attempts by researchers for more than two decades in various styles of dance all round the world, we found a review paper that portrays the research status in this area dating to 1990 \cite{politis1990computers}. Hence, we decide to come up with a comprehensive review article that showcases several aspects of dance automation. This paper is an attempt to review research work reported in the literature, categorize and group all research work completed so far in the field of automating dance. We have explicitly identified six major categories corresponding to the use of computers in dance automation namely dance representation, dance capturing, dance semantics, dance generation, dance processing approaches and applications of dance automation systems. We classified several research papers under these categories according to their research approach and functionality. With the help of proposed categories and subcategories one can easily determine the state of research and the new avenues left for exploration in the field of dance automation.

An Automated Stick Figure Generation for BharataNatyam Dance Visualization

Abstract: BharataNatyam (BN) is an ancient Indian Classical Dance dating centuries ago This unique classical dance has been taught by a teacher to a student mostly by rote learning method A student uses various methods to record the dance choreography taught by a teacher Currently recording through mobile phones and various other devices of a live dance performance are popular methods but it has its own inherent disadvantagesSeveral attempts of automation in choreography are reported and dance visualization is the key factor Stick Figure representation is a popular method amongst all and is still being used by many of the practitionersWe have developed a model to represent a BN dance step through a unique thirty attribute dance position vector Evolutionary approach of Genetic Algorithms generates non-conventional BN dance poses which are approved by renowned dance experts However, in order to visualize every resulting BN dance, a human model has to pose accordingly We overcame this hurdle by developing a stick figure generation module In this paper we present the details of stick figure and in particular how we mold it to suit to a BN dance pose that corresponds to a Dance position vector

Information Technology and the Arts: The Evolution of Computer Choreography during the Last Half Century

Abstract: This article explores the history of the relations between computer science, information technology, and the art of dance. In the early years of computer choreography, scientists envisaged the deve...

Art to SMart: An evolutionary computational model for BharataNatyam choreography

Abstract: Dance choreography is an intense, creative and intuitive process. A choreographer has to finalize appropriate dance steps from amongst millions of possibilities. Though it is not impossible, the choreographer being human cannot explore, analyze and remember all these variations among steps due to large scale of available options. Hence, we propose to simplify the problem of exploring and selecting dance steps from amongst the huge set of all possible variations for an Indian Classical Dance, BharataNatyam (BN). Based on a computational model developed by Jadhav et al. [13], we propose a Genetic Algorithm (GA) driven automatic system that would provide a list of unexplored novel dance steps to choreographers. We have incorporated certain measures to ensure that the proposed dance steps should be feasible and appropriate. In this paper, we discuss an automated approach to obtain unexplored dance steps using a proposed fitness function for a single beat/count. The details of experimental study performed for the Genetic Algorithm based art to SMart (System Modelled art) system along with the results obtained are also presented in this paper.

Digitizing Intangible Cultural Heritage Embodied: State of the Art

Abstract: Intangible cultural heritage (ICH) as a field of research and site for digital efforts has grown significantly since the UNESCO 2003 Convention for the Safeguarding of Intangible Heritage. In contrast to tangible heritage, where cultural identities are manifested through physical objects, intangible cultural expressions are defined through tacit reliances and embodied practices. Such practices are usually bodily communicated, enacted, socially transmitted, and constantly evolving. Burgeoning trends in computational heritage and ICT applications have played a crucial role in safeguarding ICH as they produce versatile resources while making them accessible to the public. Nevertheless, most of the inventions are object-centric and cater to conserving material-based knowledge bases. Few endeavors thus far have fully supported the recording, representing, and reviving of the living nature of ICH. One of the challenges now faced is to find appropriate forms, together with efficient methods, to document the ephemeral aspects of intangible heritage. Another barrier is to find effective ways to communicate the knowledge inextricably linked to people. In response, recent efforts have embarked on capturing the “live” and “active” facets of the embodied cultures, which entails addressing technological and curatorial complexity to communicate the material and immaterial aspects within a meaningful context. Meanwhile, advancements in experimental museology have opened up new modes of experiential narratives, particularly through visualization, augmentation, participation, and immersive embodiment. Novel practices of cultural data computation and data sculpting have also emerged toward the ideal of knowledge reconstruction. This article outlines state-of-the-art models, projects, and technical practices that have advanced the digitization lifecycle for ICH resources. The review focuses on several critical but less studied tasks within digital archiving, computational encoding, conceptual representation, and interactive engagement with the intangible cultural elements. We aim at identifying the advancements and gaps in the existing conventions, and to envision opportunities for transmitting embodied knowledge in intangible heritage.

Art to SMart: An Automated BharataNatyam Dance Choreography

Abstract: Hence, we propose to develop an autoenumeration followed by autoclassification of significant BN dance steps that can be used in dance performance and choreography. The foremost and most challenging task is to have a computational model that represents different BN dance poses. The second task is to develop a genetic algorithm GA-driven automatic system that would provide choreographers a list of unexplored, novel dance steps to fit in a single beat. We designed Art to SMart as a system to model the dance art of BharataNatyam. This system generates dance poses. Furthermore, we have developed a stick figure generation module to help visualize the 30-attribute dance vector generated from the system. The results are evaluated using a mean opinion score measure.

Bharata Natyam training at The Temple of Fine Arts: Pre arangetram, arangetram and post- arangetram / Bhanumathi K Nadson

Abstract: Solo debut recital called arangetram is an essential part of training in Indian classical dance, particularly, Bharata Natyam. Years of training in Bharata Natyam usually culminates with the staging of the major and sometimes “spectacle” recital, arangetram. While it is looked upon as a means to introduce the dancer to the public and launch his/her dance career, scholars of Indian dance have variously argued that arangetrams often lead to the degeneration of dance careers. However, I do not see this trend in my study which focuses on Bharata Natyam training at the Temple of Fine Arts (TFA). The TFA Kuala Lumpur was inaugurated in 1981 by its patron, the late His Holiness Swami Shantanand Saraswati. It is one of the leading institutions of Indian classical dances in Malaysia. TFA has branches in Penang, Johor Bahru, Malacca in Malaysia as well as branches in other countries such as Singapore, Colombo in Sri Lanka, Perth in Australia, Coimbatore and Chennai in Tamil Nadu, South India and in New Zealand. Bharata Natyam is the oldest and most popular Indian classical dance form taught in TFA for more than three decades now. Not only is the training unique as it adheres to the traditional guru-sishya relationship despite institutional training that is based on exams, it also provides a pathway for students to emerge as soloists and choreographers through different platforms. This study will trace that pathway by focusing on phases of pre-arangetram, arangetram, and post-arangetram. While this study highlights challenges and problems in launching a career as a performer and choreographer in Indian classical dance in Malaysia, it will also demonstrate how arangetram is a gateway that helps to shape one as a public performer. TFA goes one step further and provides a platform for its graduates to emerge as soloists, group performers, and choreographers, continuously nurturing the artistic growth of its students. In this dissertation, I will examine the training methods that culminate with TFA arangetram and further investigate what happens to dancers at post-arangetram phase by looking at several dance performances. This study draws materials from ethnographic research conducted with teachers, graduates of TFA, students, parents and management.