Development of CNN-based Virtual Mouse

Author(s):  
Mohammed Anasuddin

The technique of building a process of interaction between human and computer is evolving since the invention of technology. The mouse is a superb invention in HCI (Human-Computer Interaction) technology. Though wireless mouse technology is invented still, that technology isn't completely device free. A Bluetooth mouse has the need of battery power and connecting dongle. The proposed mouse system is beyond this limitation. This paper proposes a virtual mouse system supported HCI using computer vision and hand gestures. Gestures captured with a built-in camera or webcam and processed by a Convolutional Neural Network Model for classification among the desired mouse operations. The users are going to be allowed to regulate a number of the pc cursor functions with their hand gestures. Primarily, a user can perform left clicks, right clicks, and double clicks, scrolling up or down using their hand in several gestures. This technique captures frames employing a webcam or built-in cam and processes the frames to make them track-able and then recognizes different gestures made by users and perform the mouse functions. Therefore the proposed mouse system eliminates device dependency so as to use a mouse.

Author(s):  
Mr. Venkateshwar A

Abstract: The technique of interaction between human and computer is evolving since the invention of computer technology. The mouse is one of the invention in HCI (human computer interaction) technology. Though wireless are Bluetooth mouse technology is invented still, that technology is not completely device free. A Bluetooth mouse has the requirement of battery power it requires extra power supply. Presence of extra devices in a mouse increases the difficulty level of more hardware components. The proposed mouse system is outside this limitation. This paper proposes a virtual mouse system using colored hand glove based on HCI using computer vision and hand gestures. Gestures captured with a webcam on processed with color segmentation, detection technique and feature extraction. The user will be allowed to control some of the computer cursor functions with a colored glove on the hand. Primarily, a user can perform with their fingers, scrolling up or down using their hands in different gestures. This system captures frames using a webcam or built-in cam it is based on the camera quality. So the usage of colored glove mouse system eliminates device dependency in order to use a mouse. Keywords: HCI(human computer interaction), colored hand glove , gestures


2019 ◽  
Vol 24 (3) ◽  
pp. 220-228
Author(s):  
Gusti Alfahmi Anwar ◽  
Desti Riminarsih

Panthera merupakan genus dari keluarga kucing yang memiliki empat spesies popular yaitu, harimau, jaguar, macan tutul, singa. Singa memiliki warna keemasan dan tidak memilki motif, harimau memiliki motif loreng dengan garis-garis panjang, jaguar memiliki tubuh yang lebih besar dari pada macan tutul serta memiliki motif tutul yang lebih lebar, sedangkan macan tutul memiliki tubuh yang sedikit lebih ramping dari pada jaguar dan memiliki tutul yang tidak terlalu lebar. Pada penelitian ini dilakukan klasifikasi genus panther yaitu harimau, jaguar, macan tutul, dan singa menggunakan metode Convolutional Neural Network. Model Convolutional Neural Network yang digunakan memiliki 1 input layer, 5 convolution layer, dan 2 fully connected layer. Dataset yang digunakan berupa citra harimau, jaguar, macan tutul, dan singa. Data training terdiri dari 3840 citra, data validasi sebanyak 960 citra, dan data testing sebanyak 800 citra. Hasil akurasi dari pelatihan model untuk training yaitu 92,31% dan validasi yaitu 81,88%, pengujian model menggunakan dataset testing mendapatan hasil 68%. Hasil akurasi prediksi didapatkan dari nilai F1-Score pada pengujian didapatkan sebesar 78% untuk harimau, 70% untuk jaguar, 37% untuk macan tutul, 74% untuk singa. Macan tutul mendapatkan akurasi terendah dibandingkan 3 hewan lainnya tetapi lebih baik dibandingkan hasil penelitian sebelumnya.


2021 ◽  
Vol 1099 (1) ◽  
pp. 012001
Author(s):  
Srishti Garg ◽  
Tanishq Sehga ◽  
Aakriti Jain ◽  
Yash Garg ◽  
Preeti Nagrath ◽  
...  

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