Graffiti-writing recognition with fine-grained information
by Jiashuang Xu; Zhangjie Fu; Xingyue Du
International Journal of Computational Science and Engineering (IJCSE), Vol. 21, No. 2, 2020

Abstract: Currently, the contactless human-computer interaction (HCI) has become a heated research topic due to the springing up of the novel intelligent terminals. The existing interaction systems are used to adopt depth cameras, motion controller, radio frequency devices. The common drawback of the above approaches is that all the participants are required to obey the unistroke writing standard for data acquisition. Thus, we are motivated to propose a more adaptive, contactless graffiti-writing recognition system with channel state information (CSI) derived from Wi-Fi signals. We extract the unique CSI waveform caused by writing action to represent each letter. To cater to more users' writing customs, we train separate hidden Markov model (HMM) for eight of 26 letters and conduct cross-validation for testing. The average detection accuracy reaches 94.5%. The average recognition accuracy for the 26-letter model is 85.96% when the number of training samples is 100 from five subjects. The real-time recognition efficiency measured by characters per minute (CPM) is 11.97 (= 31/155.24 s).

Online publication date: Fri, 06-Mar-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Science and Engineering (IJCSE):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com