Invited Speaker
Prof. Narendra D. Londhe

Prof. Narendra D. Londhe

Associate Professor, Department of Electrical Engineering of National Institute of Technology Raipur, Chhattisgarh INDIA
Speech Title: MVFNet: A multi-view fusion network for pain intensity assessment in unconstrained environment

Abstract: Pain is an indication of physical discomfort, and its monitoring is crucial for medical diagnosis and treatment of the patient. In the past few years, several techniques have been proposed for pain assessment from face images. Although existing approaches provide satisfactory performance on constrained frontal faces, they might perform poorly in the natural unconstrained hospital environment due to low illumination conditions, large head-pose rotation, and occlusion which is common in an unconstrained environment. Therefore, a novel fusion approach to constitute discriminative features for pain severity assessment is proposed. In this work, decision level fusion of three distinct features, i.e., data-driven RGB features, entropy based texture features, and complementary features learned from both RGB and texture data are utilized to improve the generalization of the proposed pain assessment system. The experimental results demonstrate that the decision level fusion using these Multi-view features substantially outperforms the model trained with generic RGB data. Given this, the proposed system utilizes three CNNs, i.e., VGG-CNN based on cross dataset Transfer Learning (VGG-TL), Entropy Texture Network (ETNet), and Dual Stream CNN (DSCNN). Further, to alleviate the problem of overfitting various augmentation techniques are implemented. Furthermore, the proposed approach has been assessed extensively on self-generated datasets of 10 patients recorded in an unconstrained hospital environment. The experimental results demonstrate that the proposed model achieved 94.0 % of F1-score for pain severity assessment. In addition, to evaluate the generalization of the proposed method we also report competitive results in the UNBC-McMaster dataset.

Biography: Narendra D. Londhe is presently working as Associate Professor in the Department of Electrical Engineering of National Institute of Technology Raipur, Chhattisgarh INDIA. He completed his B.E. from Amravati University in 2000 followed by M.Tech and Ph.D. from Indian Institute of Technology Roorkee in the year 2006 and 2011 respectively. He has 14 years of rich experience in academics and research. He has published more than 150 articles in recognized journals, conferences, and books. His main areas of research include Medical Signal and Image Processing, Biomedical Instrumentation, Speech Signal Processing, Biometrics, Intelligent Healthcare, Brain Computer Interface, Artificial Intelligence and Pattern Recognition. He has been awarded by organizations like Taiwan Society of Ultrasound in Medicine, Ultrasonics Society of India, and NIT Raipur. He is an active member of different recognized societies from his areas of research including senior membership of IEEE.