Skip navigation
Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/5642
Title: 3D text segmentation and recognition using leap motion
Authors: Kumar P.
Saini R.
Pratim Roy, Partha
Dogra D.P.
Published in: Multimedia Tools and Applications
Abstract: In this paper, we present a method of Human-Computer-Interaction (HCI) through 3D air-writing. Our proposed method includes a natural way of interaction without pen and paper. The online texts are drawn on air by 3D gestures using fingertip within the field of view of a Leap motion sensor. The texts consist of single stroke only. Hence gaps between adjacent words are usually absent. This makes the system different as compared to the conventional 2D writing using pen and paper. We have collected a dataset that comprises with 320 Latin sentences. We have used a heuristic to segment 3D words from sentences. Subsequently, we present a methodology to segment continuous 3D strokes into lines of texts by finding large gaps between the end and start of the lines. This is followed by segmentation of the text lines into words. In the next phase, a Hidden Markov Model (HMM) based classifier is used to recognize 3D sequences of segmented words. We have used dynamic as well as simple features for classification. We have recorded an overall accuracy of 80.3 % in word segmentation. Recognition accuracies of 92.73 % and 90.24 % have been recorded when tested with dynamic and simple features, respectively. The results show that the Leap motion device can be a low-cost but useful solution for inputting text naturally as compared to conventional systems. In future, this may be extended such that the system can successfully work on cluttered gestures. © 2016, Springer Science+Business Media New York.
Citation: Multimedia Tools and Applications (2017), 76(15): 16491-16510
URI: https://doi.org/10.1007/s11042-016-3923-z
http://repository.iitr.ac.in/handle/123456789/5642
Issue Date: 2017
Publisher: Springer New York LLC
Keywords: 3D air-writing
Dynamic features
Gesture on air
Touchless interfaces
Written text segmentation
ISSN: 13807501
Author Scopus IDs: 57212043589
57190288840
56880478500
35408975400
Author Affiliations: Kumar, P., Department of Computer Science and Engineering, Indian Institutes of Technology, Roorkee, India
Saini, R., Department of Computer Science and Engineering, Indian Institutes of Technology, Roorkee, India
Roy, P.P., Department of Computer Science and Engineering, Indian Institutes of Technology, Roorkee, India
Dogra, D.P., School of Electrical Sciences, Indian Institutes of Technology, Bhubaneswar, India
Corresponding Author: Dogra, D.P.; School of Electrical Sciences, Indian Institutes of TechnologyIndia; email: dpdogra@iitbbs.ac.in
Appears in Collections:Journal Publications [CS]

Files in This Item:
There are no files associated with this item.
Show full item record


Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.