Faculty Publications
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Publications by NITK Faculty
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Item A novel real-time face detection system using modified affine transformation and Haar cascades(Springer Verlag service@springer.de, 2019) Sharma, R.; Ashwin, T.S.; Guddeti, R.M.R.Human Face Detection is an important problem in the area of Computer Vision. Several approaches are used to detect the face for a given frame of an image but most of them fail to detect the faces which are tilted, occluded, or with different illuminations. In this paper, we propose a novel real-time face detection system which detects the faces that are tilted, occluded, or with different illuminations, any difficult pose. The proposed system is a desktop application with a user interface that not only collects the images from web camera but also detects the faces in the image using a Haar-cascaded classifier consisting of Modified Census Transform features. The problem with cascaded classifier is that it does not detect the tilted or occluded faces with different illuminations. Hence to overcome this problem, we proposed a system using Modified Affine Transformation with Viola Jones. Experimental results demonstrate that proposed face detection system outperforms Viola–Jones method by 6% (99.7% accuracy for the proposed system when compare to 93.5% for Voila Jones) with respect to three different datasets namely FDDB, YALE and “Google top 25 ‘tilted face’” image datasets. © Springer Nature Singapore Pte Ltd. 2019Item Stability Analysis of Emerged Seaside Perforated Quarter Circle Breakwater Using Soft Computing Techniques(Springer Science and Business Media Deutschland GmbH, 2022) Madhusoodhanan, S.; Rao, S.Breakwaters are constructed to address a variety of coastal requirements ranging from maintaining tranquility conditions for a port or harbor area to prevent coastal recession. Quarter circle breakwater (QCB) is a composite structure, with a rubble mound foundation and a super structure comprising of a quarter circular surface facing incident waves resting on a horizontal bottom with a rear vertical wall alongside. Be it any structure, it is essential that the design is economic, safe, and functional. Thus, the accurate estimation of minimum (critical) weight of the super structure required to oppose the sliding is vital. Also, physical model studies can be laborious and time-consuming, whereas numerical modeling can be complex. Therefore, under such circumstances, soft computing techniques prove to be handy if sufficient data are available. In this study, W/γHi 2 of an emerged seaside perforated QCB for varying S/D ratios is estimated using ANN, SVM, and AdaBoost models. Hi/gT2, d/hs, and p (%) are chosen as input parameters with the W/γHi 2 as the output parameter. Further, the obtained results are compared using performance indicators such as RMSE, R2, and MAE following which the best model is selected. The data that are used for the present study is collected from the laboratory investigation conducted in the Wave Mechanics Laboratory of the Department of Water Resources and Ocean Engineering, National Institute of Technology Karnataka, Surathkal. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Estimation of Tyre Pressure from the Characteristics of the Wheel: An Image Processing Approach(Springer, 2020) Vineeth Reddy, V.B.; Ananda Rao, H.; Yeshwanth, A.; Ramteke, P.B.; Koolagudi, S.G.Improper tyre pressure is a safety issue that falls prey to ignorance of users. But a drop in tyre pressure can result in the reduction of mileage, tyre life, vehicle safety and performance. In this paper, an approach is proposed to measure the tyre pressure from the image of the wheel. The tyre pressure is classified into under pressure and normal pressure using load index, tyre type, tyre position and ratio of compressed and uncompressed tyre radius. The efficiency of the feature is evaluated using three classifiers namely Random Forest, AdaBoost and Artificial Neural Networks. It is observed that the ratio of radii plays a major role in classifying the tyres. The proposed system can be used to obtain a rough idea on whether the tyre should be refilled or not. © 2020, Springer Nature Singapore Pte Ltd.Item NBA MVP Prediction and Historical Analysis Using Cross-Era Comparison Approaches(Institute of Electrical and Electronics Engineers Inc., 2024) Godbole, I.; Murali, S.S.; Sowmya Kamath, S.In order to understand the crucial player statistics that decide the Most Valuable Player (MVP) Trophy, this research study dives into a substantial 32-year dataset of the National Basketball Association (NBA). We build a predictive framework trained on historical player statistics and MVP voting results using a sophisticated ensemble of machine learning models, including Support Vector Machines (SVM), ElasticNet, AdaBoost, Random Forest and Back-propagation Neural Network (BP). We determine the key elements influencing this renowned award by evaluating connections between player stats and MVP picks. Our research provides insights into the MVP selection process by utilising the models' ability to capture complex patterns and nonlinear interactions, providing stakeholders with a reliable tool for assessing player performances.This work advances the discourse surrounding the NBA MVP Trophy and enriches our comprehension of player value assessment. Also, the prediction models are used to conduct various historical analysis experiments, by finding an objective method to compare performances of players from different eras. © 2024 IEEE.