Search Results - "Teja Kiran Kumar, M."

Unifying Boundary, Region, Shape into Level Sets for Touching Object Segmentation in Train Rolling Stock High Speed Video by Sasikala, N., Kishore, P.V.V., Prasad, Ch. Raghava, Kumar, E. Kiran, Kumar, D. Anil, Kiran Kumar, M. Teja, Prasad, M.V.D.

“…Traditional level sets suffer from two major limitations: 1) unable to detect touching object boundaries and 2) segment partially occluded objects. In this…”
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Early estimation model for 3D-discrete indian sign language recognition using graph matching by Kiran Kumar, E., Kishore, P.V.V., Anil Kumar, D., Teja Kiran Kumar, M.

“…Machine translation of sign language is a critical task of computer vision. In this work, we propose to use 3D motion capture technology for sign capture and…”
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Can Skeletal Joint Positional Ordering Influence Action Recognition on Spectrally Graded CNNs: A Perspective on Achieving Joint Order Independent Learning by Kumar, M. Teja Kiran, Kishore, P. V. V., Madhav, B. T. P., Kumar, D. Anil, Kala, N. Sasi, Rao, K. Praveen Kumar, Prasad, B.

“…3D skeletal based action recognition is being practiced with features extracted from joint positional sequence modeling on deep learning frameworks. However,…”
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3D sign language recognition with joint distance and angular coded color topographical descriptor on a 2 – stream CNN by Kumar, E. Kiran, Kishore, P.V.V., Kiran Kumar, M. Teja, Kumar, D. Anil

“…Currently, one of the challenging and most interesting human action recognition (HAR) problems is the 3D sign language recognition problem. The sign in the 3D…”
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S3DRGF: Spatial 3-D Relational Geometric Features for 3-D Sign Language Representation and Recognition by Kumar, D. Anil, Sastry, A. S. C. S., Kishore, P. V. V., Kumar, E. Kiran, Kumar, M. Teja Kiran

“…Locations, angles, edges, and surfaces are spatial joint features that were predominantly used for characterizing three-dimensional (3-D) skeletal data in…”
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Multi modal spatio temporal co-trained CNNs with single modal testing on RGB–D based sign language gesture recognition by Ravi, Sunitha, Suman, Maloji, Kishore, P.V.V., Kumar E, Kiran, Kumar M, Teja Kiran, Kumar D, Anil

“…•RGB-D based Indian sign language model is being developed.•RGB and depth data are used to train the proposed convolutional neural network with data sharing…”
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A four-stream ConvNet based on spatial and depth flow for human action classification using RGB-D data by Srihari, D., Kishore, P. V. V., Kumar, E. Kiran, Kumar, D. Anil, Kumar, M. Teja Kiran, Prasad, M. V. D., Prasad, Ch. Raghava

“…Appearance and depth-based action recognition has been researched exclusively for improving recognition accuracy by considering motion and shape recovery…”
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Training CNNs for 3-D Sign Language Recognition With Color Texture Coded Joint Angular Displacement Maps by Kumar, E. Kiran, Kishore, P. V. V., Sastry, A. S. C. S., Kumar, M. Teja Kiran, Kumar, D. Anil

“…Convolutional neural networks (CNNs) can be remarkably effective for recognizing two-dimensional and three-dimensional (3-D) actions. To further explore the…”
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A Quad Joint Relational Feature for 3D Skeletal Action Recognition with Circular CNNs by Kishore, P. V. V., Perera, Darshika. G., Kumar, M. Teja Kiran, Kumar, D. Anil, Kumar, E. Kiran

“…To deal with the limitations of human action recognition systems that apply deep neural networks (DNNs) to 3D skeletal feature maps, we propose an improved set…”
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Investigation of 3-D Relational Geometric Features for Kernel-Based 3-D Sign Language Recognition by Kiran, P. Sasi, Kumar, D. Anil, Kishore, P.V.V., Kumar, E. Kiran, Kumar, M. Teja Kiran, Sastry, A.S.C.S.

“…Extraction and recognition of human gestures in 3D sign language is a challenging task. 3D sign language gestures are a set of hand and finger movements with…”
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