Digital Yoga Game with Enhanced Pose Grading Model

Sharma, Konark; Agarwal, Vedangi; Rajpoot, Abha Kiran

doi:10.1109/iccsea54677.2022.9936591

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…For example, the article [16] presents a method for recognizing different dance poses. The paper [19] examines a new computer vision-based transformation model for human pose estimation and proposes a game that allows users to learn yoga practices.…”

Section: Source: Compiled By the Authorsmentioning

confidence: 99%

The method of automated filling of the database with descriptions of human physical exercises

Volkov,

Blazhko

2024

HAIT

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Presently, human-computer interaction employs infrared cameras equipped with motion tracking capabilities, facilitating the automatic generation of spatial descriptions for multiple human joints. The use of such cameras allows for the creation of active computer games, where the player can control the game process by performing physical exercises or specific gestures. The study examined support systems for computer games with physical exercises and identified the lack of an ability to modify the description of physical exercises in a separate database. The authors created a prototype for a computer game that incorporates physical exercises, storing them in the database as a series of gestures. However, the experiments revealed several drawbacks: the requirement for a specialist to independently populate the database with physical exercise descriptions, the potential for errors in the analysis of physical exercises, and the labor-intensive process of database filling. Therefore, the goal of this work was to reduce the time required to populate the database for identifying human physical exercises based on the spatial description of multiple joints formed by the infrared camera. To achieve this goal, the authors proposed the creation of a visual constructor for physical exercises and a method for automating the database's recognition of physical exercises. The practical significance of the work is as follows, the authors developed software, that includes the following steps: saving the states of joint positions over a specified period, processing the obtained joint state data from the spatial description, determining the logical relationships between the joints (greater, less, or equal), removing duplicate descriptions, identifying errors by the specialist using the visual constructor for physical exercises, and populating the database. The article examined the labor intensity of manually populating the database and the proposed method using physical exercises containing three, five, seven, and ten gestures. The results of the analysis showed a reduction in the labor intensity of populating the database using the proposed method by two point six to three point six times, depending on the complexity and specifics of the physical exercise. All experiments in the work were conducted using the Microsoft Kinect 2, which has been discontinued, but this does not affect the relevance of the work, as Microsoft encourages developers to continue using the existing Kinect Developer Kit programming environment for the Femto Bolt and Femto Mega infrared cameras from Orbex.

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Section: Source: Compiled By the Authorsmentioning

confidence: 99%

The method of automated filling of the database with descriptions of human physical exercises

Volkov,

Blazhko

2024

HAIT

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“…Yoga adalah sebuah aktivitas yang mengarahkan seseorang untuk berkonsentrasi, mengatur nafas, menenangkan pikiran dengan pose-pose tertentu [1], [2]. Gerakan pose yoga yang benar memang telah terbukti dalam pengaruh positif bagi berbagai macam kehidupan manusia [3], [4]. Dalam melakukan aktivitas yoga, banyak para yogis (seseorang yang melakukan yoga) yang melakukannya sendiri dari rumah melalui panduan-panduan yoga yang ada atau melakukan yoga bersama melalui virtual dengan orang lain menggunakan instruktur yoga dan jika melakukan tanpa instruktur, yogis bisa mengikuti panduan yoga yang sudah ada berupa gambar dua dimensi atau video dan audio yang dapat membantu [5].…”

Section: Pendahuluanunclassified

Penerapan Metode Posenet untuk Deteksi Ketepatan Pose Yoga

Ahmad Asshidiqy,

Setiawan,

Sasongko

2022

JoSYC

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When someone does yoga activities, usually, someone follows yoga guidelines in the form of yoga classes and yoga self-guidance, which is usually in the form of images, videos, and audio. But along with the rapid development of technology, now there are many yoga guides and easy to get. Yoga activities can now be done independently without approaching a yoga instructor. The purpose of this study is to help yogis to be able to do yoga correctly and to follow yoga guidelines with the correct poses with a system that contains yoga poses and also as the main feature of correcting yoga poses that yogis do to get yoga poses correctly. The resulting system will capture yoga poses and detect whether the pose is correct according to the yoga pose guidelines. Based on the verification of the distance between the device or the device that has a camera, it is placed at a distance of 200cm – 250cm between the device and the yogis. The device's height is placed in a place that has a height half the size of the yogi's whole body or at the height of 85cm. The test results using the BlackBox method get no errors. Besides that, the system can run well in a room with 7-watt LED lights, and no objects block the yogis, so the camera catches the whole body.

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Digital Yoga Game with Enhanced Pose Grading Model

Cited by 2 publications

References 12 publications

The method of automated filling of the database with descriptions of human physical exercises

The method of automated filling of the database with descriptions of human physical exercises

Penerapan Metode Posenet untuk Deteksi Ketepatan Pose Yoga

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