Buddhist Hasta Mudra Recognition Using Morphological Features
@inproceedings{Bhaumik2020BuddhistHM, title={Buddhist Hasta Mudra Recognition Using Morphological Features}, author={Gopa Bhaumik and Mahesh Chandra Govil}, booktitle={ICML 2020}, year={2020} }
Mudras are considered as spiritual gestures in the religious sense and hold a very important place in the cultural and spiritual space in India. Images are the symbolic representations of divinity in religious artwork and their origins are conveyed through the religions and spiritual beliefs. Such gestures also have some specific meaning in the Buddhist religion. It refers to some of the events in the life of Buddha or denotes special characteristics of the Buddha deities. In recent years…
References
SHOWING 1-10 OF 15 REFERENCES
“Hasta Mudra”: An interpretation of Indian sign hand gestures
- Computer Science2011 3rd International Conference on Electronics Computer Technology
- 2011
This paper has summarized the study of Indian sign language and its varieties and a simple recognition system is proposed to create a system which can identify gestures of human hand and use them to convey information without the use of interpreter.
Indian Classical Dance Mudra Classification Using HOG Features and SVM Classifier
- Computer Science
- 2017
This work explores the possibilities of recognizing classical dance mudras in various dance forms in India and helps new learners and dance enthusiastic people to learn and understand dance forms and related information on their mobile devices.
Research on Tibet Tangka based on shape grammar
- Art2008 9th International Conference on Computer-Aided Industrial Design and Conceptual Design
- 2008
Introduce a new research method which based on shape grammar for depth analysis of art of Tibetan Tangka paintings. As an important components of painting art of Tibet, although Tangka paintings is…
Leaf Morphological Feature Extraction of Digital Image Anthocephalus Cadamba
- Computer Science
- 2016
This research implemented an image feature extraction method using morphological techniques. The goal of this proccess is detecting objects that exist in the image. The image is converted into a…
Dance Gesture Recognition: A Survey
- Psychology, Computer Science
- 2015
This survey is to present a comprehensive survey on automated dance gesture recognition with emphasis on static hand gesture recognition, considering human hands because human hands are the most flexible part of the body and can transfer the most meaning.
An Improved morphological component analysis algorithm for Tangka image inpainting
- Computer Science2013 6th International Congress on Image and Signal Processing (CISP)
- 2013
A new image inpainting method based on morphological component analysis that is capable of filling in holes in overlapping texture and cartoon layers is proposed, and the concept of an example patches-aided dictionary learning algorithm named KSVD algorithm is adopted.
Headdress Detection Based on Saliency Map for Thangka Portrait Image
- Computer ScienceMVA
- 2011
The saliency map of attention model is applied on Thangka image detection for the first time and gives new thought to automatic image segmentation, not only for Thangkaka image, but also for other kinds of research objects.
Classification and Regression by randomForest
- Computer Science
- 2007
random forests are proposed, which add an additional layer of randomness to bagging and are robust against overfitting, and the randomForest package provides an R interface to the Fortran programs by Breiman and Cutler.
A Plant Identification System using Shape and Morphological Features on Segmented Leaflets: Team IITK, CLEF 2012
- Computer ScienceCLEF
- 2012
This paper describes team IITK’s participation in the Plant Identification Task, CLEF 2012, organized by the Combined Lab Evaluation Forum (CLEF), where the challenge was to identify plant species based on leaf images.
Two-Dimensional Linear Discriminant Analysis
- Computer ScienceNIPS
- 2004
2DLDA, a novel LDA algorithm, which stands for 2-Dimensional Linear Discriminant Analysis, overcomes the singularity problem implicitly, while achieving efficiency and the combination of 2DLDA and classical LDA, namely 2 DLDA+LDA, is studied.