OpenCV Image Processing for AI Pet Robot

Abhishek Manajit Ghoshal; Aditya Aspat; Elton Lemos

doi:10.24071/ijasst.v3i1.2765

OpenCV Image Processing for AI Pet Robot

Abhishek Manajit Ghoshal, Aditya Aspat, Elton Lemos

Abstract

The Artificial Intelligence (AI) Pet Robot is a culmination of multiple fields of computer science. This paper showcases the capabilities of our robot. Most of the functionalities stem from image processing made available through OpenCV. The functions of the robot discussed in this paper are face tracking, emotion recognition and a colour-based follow routine. Face tracking allows the robot to keep the face of the user constantly in the frame to allow capturing of facial data. Using this data, emotion recognition achieved an accuracy of 66% on the FER-2013 dataset. The colour-based follow routine enables the robot to follow the user as they walk based on the presence of a specific colour.

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References

Center for Disease Control and Prevention, Healthy Pets, Healthy People, https://www.cdc.gov/healthypets/health-benefits/index.html, Accessed: 12/01/2020

E. Paul Cherniack, MD and Ariella R. Cherniack, Assessing the benefits and risks of owning a pet, Canadian Medical Association Journal, July 14, 2015

Paul Viola and Michael Jones, Rapid Object Detection using a Boosted Cascade of Simple Features, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, Volume 1, 2001

Challenges in Representation Learning: Facial Expression Recognition Challenge, https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data, 2013.

Nishchal Poornadithya C., P.Chimanna Chengappa, Thangaraj Raman, Shantanu Pandey & Gopal Krishna Shyam ,Emotion Identification and Classification using Convolutional Neural Networks , International Journal of Advanced Research in Computer Science, 2018

Rutger Ruizendaal, Deep Learning #3: More on CNNs Handling Overfitting, https://towardsdatascience.com/deep-learning-3-more-on-cnns-handling-overfitting-2bd5d99abe5d, 2017, Accessed 23/02/2020.

Adrian Rosebrock, Ball Tracking with OpenCV, https://www.pyimagesearch.com/2015/09/14/ball-tracking-with-opencv/, 2015, Accessed 02/02/2020

Renu Khandelwal, L1 and L2 Regularization, https://medium.com/datadriveninvestor/l1-l2-regularization-7f1b4fe948f2, Nov 4, 2018, Accessed 23/02/2020

DOI: https://doi.org/10.24071/ijasst.v3i1.2765