BITS Faculty Publications
Permanent URI for this communityhttp://localhost:4000/handle/123456789/1867
Browse
3 results
Search Results
Item Advancements in Yoga Pose Estimation Using Artificial Intelligence: A Survey(Bentham Science, 2024) Chamola, Vinay; Rout, Bijay KumarHuman pose estimation has been a prevalent field of computer vision and sensing study. In recent years, it has made many advances that have helped humanity in the fields of sports, surveillance, healthcare, etc. Yoga is an ancient science intended to improve physical, mental and spiritual wellbeing. It involves many kinds of asanas or postures that a practitioner can perform. Thus, the benefits of pose estimation can also be used for Yoga to help users assume Yoga postures with better accuracy. The Yoga practitioner can detect their own current posture in real-time, and the pose estimation method can provide them with corrective feedback if they commit mistakes. Yoga pose estimation can also help with remote Yoga instruction by the expert teacher, which can be a boon during a pandemic. This paper reviews various Machine Learning, Artificial Intelligence-enabled techniques available for real-time pose estimation and research pursued recently. We classify them based on the input they use for estimating the individual's pose. We also discuss multiple Yoga posture estimation systems in detail. We discuss the most commonly used keypoint estimation techniques in the existing literature. In addition to this, we discuss the real-time performance of the presented works. The paper further discusses the datasets and evaluation metrics available for pose estimation.Item Hyper-parameter Optimization on Viola Jones Algorithm for Gesture Recognition(Springer, 2020-07) Rout, Bijay KumarThe problem of features, objects, gestures, and face detection has been tackled using a numerous vision-based algorithms available in literature. Each of these algorithms requires a set of hyper-parameters, which need to be set on the basis of trial and error such that the results provide best performance to a situation. Mostly, researchers use trial and error approach to satisfactory result and solve the above problems. In this work, an approach has been suggested to determine an optimum set of hyper-parameters, which will provide a starting point for anyone using Viola Jones algorithm for hand gesture recognition or similar endeavors. This will reduce the time spent in searching for the best combination of hyper-parameters.Item NDENet: End-to-End Nighttime Dehazing and Enhancement(World Academy of Science, Engineering and Technology, 2007-01) Rout, Bijay KumarIn this paper, we present a computer vision task called nighttime dehaze-enhancement. This task aims to jointly perform dehazing and lightness enhancement. Our task fundamentally differs from nighttime dehazing – our goal is to jointly dehaze and enhance scenes, while nighttime dehazing aims to dehaze scenes under a nighttime setting. In order to facilitate further research on this task, we release a benchmark dataset called Reside-β Night dataset, consisting of 4122 nighttime hazed images from 2061 scenes and 2061 ground truth images. Moreover, we also propose a network called NDENet (Nighttime Dehaze-Enhancement Network), which jointly performs dehazing and low-light enhancement in an end-to-end manner. We evaluate our method on the proposed benchmark and achieve Structural Index Similarity (SSIM) of 0.8962 and Peak Signal to Noise Ratio (PSNR) of 26.25. We also compare our network with other baseline networks on our benchmark to demonstrate the effectiveness of our approach. We believe that nighttime dehaze-enhancement is an essential task particularly for autonomous navigation applications, and hope that our work will open up new frontiers in research. The code for our network is made publicly available.