2. Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/1/7
Browse
28 results
Search Results
Item Recent trends in content-based video copy detection(2010) Roopalakshmi, R.; Ram Mohana Reddy, GuddetiVideo copy detection is an interesting & challenging problem, as it is becoming increasingly important with the growing rate of illegal digital media and huge piracy issues. Therefore, in the present era of Internet &Multimedia technologies,the existence of ubiquitous digital videos, has led to the requirement of robust video copy detection techniques, for content management and copyright protection. In this paper, an overview of content based video copy detection (CBVCD) is presented along with the different state-of-the-art techniques used for video feature/ signature description. This article also explores the future key directions and highlights the research challenges that need to be addressed in the CBVCD paradigm. � 2010 IEEE.Item Recent advances and future potential of computer aided diagnosis of liver cancer on computed tomography images(2011) Megha, P.A.; Ram Mohana Reddy, GuddetiLiver cancer has been known as one of the deadliest diseases. It has become a major health issue in the world over the past 30 years and its occurrence has increased in the recent years. Early detection is necessary to diagnose and cure liver cancer. Advances in medical imaging and image processing techniques have greatly enhanced interpretation of medical images. Computer aided diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver cancer and hence reduce death rate. The concept of computer aided diagnosis is to provide a computer output as a second opinion in analysis of liver cancer. It assists radiologist's image interpretation by improving accuracy and consistency of radiological diagnosis and also by reducing image analysis time. The main objective of this paper is to provide an overview of recent advances in the development of CAD systems for analysis of liver cancer. Medical imaging system based on computer tomography will be focused as it is particularly suitable for detecting liver tumors. The paper begins with introduction to liver tumors and medical imaging techniques. Then the key CAD techniques developed recently for liver tumor detection, classification, case-based reasoning based on image retrieval and 3D reconstruction are presented. This article also explores the future key directions and highlights the research challenges that need to be addressed in the development of CAD system which can help the radiologist in improving the diagnostic accuracy. � Springer-Verlag 2011.Item Projection and interaction with ad-hoc interfaces on non-planar surfaces(2013) Dere, K.S.; Ram Mohana Reddy, GuddetiProjector-based display systems have been used in area of computer interaction as Ad-hoc interface in recent time. The mobile hand-held projectors are becoming more popular. Many human centric user interfaces with the human wearable computer are being developed. Most of such system uses daily objects for projection and the interaction. But most of ignores the fact that these object surfaces are not planar. Hence such interfaces suffers from the distortion due to non-planar projection surface. Besides this projection quality also suffers from the radiometric distortion as well. Further more the interaction proposed with such interfaces bound to the planar surface only. Hence this paper is targeted to address the geometric distortion free projection of and interaction with such interfaces on non planar surfaces. Kinect is used as depth sensor for 3D scenario acquisition. We use imageper warping to mesh from Kinect. We use colored fingertip gloves for interaction. Here our system aims any day to day object surface for distortion free projection such as human body, curved wall, room corners, curtain's and many more objects. � 2013 IEEE.Item Primary education for the specially-abled(2013) Chandra, S.; Sagar, M.; Rout, P.; Khattri, P.; Domanal, S.; Ram Mohana Reddy, GuddetiTechnology can support the children who require special needs, who if given the proper training and opportunity, can compete on a basis of equality with their peers. This should be the basic philosophy of a programmer who designs programs, standards for programs, or evaluation of programs. Proper education for these children will lead to enhancing their capability to lead a dignified life and also help them to earn a square meal. Technology is needed to teach them and hence the necessity can clearly be seen for further research and development in this field. In addition to software being used as teaching tools at schools and at-home, the learning process should be more interesting so that child should feel engaged. A daily routine, not only a syllabus/homework, using technologies such as text to speech conversion and image morphology is needed to both help them understand concepts of classroom syllabus and motivate them to learn more at home as specially-abled children need to be given enough motivation, as well as time, to succeed. The system developed proves to be useful to specially-abled children to memorize rhymes, recognize common sounds (like that of animals) as well as develop haptic abilities using a game like interface. � 2013 IEEE.Item Parallelized K-Means clustering algorithm for self aware mobile Ad-hoc networks(2011) Thomas, L.; Manjappa, K.; Annappa, B.; Ram Mohana Reddy, GuddetiProviding Quality of Service (QoS) in Mobile Ad-hoc Network (MANET) in terms of bandwidth, delay, jitter, throughput etc., is critical and challenging issue because of node mobility and the shared medium. The work in this paper predicts the best effective cluster while taking QoS parameters into account. The proposed work uses K-Means clustering algorithm for automatically discovering clusters from large data repositories. Further, iterative K-Means clustering algorithm is parallelized using Map-Reduce technique in order to improve the computational efficiency and thereby predicting the best effective cluster. Hence, parallel K-Means algorithm is explored for finding the best effective cluster containing the hops which lies in the best cluster with the best throughput in self aware MANET. Copyright � 2011 ACM.Item Parallel implementation of 3D modelling of indoor environment using Microsoft Kinect sensor(2013) Manojkumar, P.; Ram Mohana Reddy, Guddeti3D visual modelling of indoor space will not only provide the detailed knowledge about the environment but also rich contextual information of the existing objects. In this paper, we propose a parallel implementation of 3D modelling of indoor environment using Microsoft Kinect depth camera. 3D maps are generated by Simultaneous Localization And Mapping [SLAM] technique. These 3-D maps will be more useful in Context aware and in Robotics applications. Iterative Closest Point [ICP] with initial guess by RANSAC is used for pair alignment. Many tasks of pair registration are parallelised using OpenMP and the performance evaluation of both sequential and parallel implementations are compared. Simulation results demonstrate that OpenMP based parallel implementation has achieved a speedup factor of 3.7. � 2013 IEEE.Item Optimized Termite: A bio-inspired routing algorithm for MANET's(2012) Hoolimath, P.K.G.; Kiran, M.; Ram Mohana Reddy, GuddetiA Mobile Adhoc Network (MANET) is a collection of mobile nodes connected by the Wireless medium and each mobile node is aware of only its neighbours. Due to mobility of these mobile nodes the topology changes dynamically. Such a dynamic network topology makes the task of routing a challenging one. Recently, a new class of routing algorithms based on Swarm Intelligence has emerged. These algorithms are inspired by nature's self-organizing systems like ant-colonies, bird-flocks, honey-bees, school of fish, spiders and fireflies. The characteristics of such algorithms are their capability of self-organization, adaptation to the changing conditions, self healing and local decision making. In this work, a routing protocol inspired by the termite activity in nature, called Optimized-Termite (Opt-Termite), is proposed. Opt-Termite uses concept of stigmergy for self-organization, thereby reducing the control packet overhead. Opt-Termite mainly concentrates on load balancing for optimization. With Opt-Termite, a route with less loaded mobile nodes in terms of traffic will be chosen to reach destination. The routing information at each node gets influenced by the movement of packets and the routing table will be updated accordingly. It also allows the use of multiple paths and each packet is routed randomly and independently. Opt-Termite is implemented in ns-2 and its performance is compared with traditional routing protocol AODV. Opt-Termite's performance has been promising. � 2012 IEEE.Item Medical image retrieval system for diagnosis of brain tumor based on classification and content similarity(2012) Arakeri, M.P.; Ram Mohana Reddy, GuddetiAccurate diagnosis is important for successful treatment of brain tumor. Content based medical image retrieval (CBMIR) can assist the radiologist in diagnosis of brain tumor by retrieving similar images from medical image database. Magnetic resonance imaging (MRI) is the most commonly used modality for imaging brain tumors. During image acquisition there can be misalignment of magnetic resonance (MR) image slices due to movement of patient and also the low level features extracted from MR image may not correspond with the high level semantics of brain tumor. These problems create a semantic gap and limit the application of automated image analysis tools on MR images. In order to address these problems, this paper proposes a two-level hierarchical CBMIR system which first classifies the query image of brain tumor as benign or malign and then searches for the most similar images within the identified class. Separate set of rotation invariant shape and texture features are used to discriminate between brain tumors at each level. Experiments have been conducted on medical image database consisting of 820 brain MR images. The proposed approach gives promising retrieval results by improving precision, recall and retrieval time. � 2012 IEEE.Item Learner centered design approach for E-learning using 3D virtual tutors(2013) Mukherjee, S.; Singhal, H.; Jha, P.; Kokane, A.; Rastogi, P.; Mittal, R.; Ram Mohana Reddy, GuddetiMost of the existing E-learning system designs have focused on the development of feature-rich, but usable systems with little effort in motivating students to develop interest in the teaching-learning process. This paper discusses the learner centered design approach for web-based tutoring to motivate young learners using 3D virtual tutors in a requirement-based, flexible pedagogical model. Students can choose course(s) and the study-mode. In the guided mode, the student is mentored by a human tutor, whereas a student in un-guided mode is tutored by 3D avatar. The student has access to study materials, educational videos and applets that are provided by the tutors, the student also has access to forums for doubt clearing and online assignments to be submitted for tutors' evaluation. Tutors can track students' progress using online quiz and reports modules. Further, tutors have access to teaching aids like online chat system and whiteboard-based teaching in a virtual classroom environment. � 2013 IEEE.Item Kinect based real-time gesture spotting using HCRF(2013) Chikkanna, M.; Ram Mohana Reddy, GuddetiThe sign language is an effective way of communication for deaf and dumb people. This paper proposes, developing the gesture spotting algorithm for Indian Sign Language that acquires sensory information from Microsoft Kinect Sensor. Our framework consists of three main stages: hand tracking, feature extraction and classification. In the first stage, hand tracking is carried out using frames of Kinect. In second stage, the features of Cartesian system (velocity, angle, location) and hand with respect to body are extracted. K-means is used for extracting the codewords of features for HCRF. In the third stage, Hidden Conditional Random Field is used for classification. The experimental results show that HCRF algorithm gives 95.20% recognition rate for the test data. In real-time, the recognition rate achieves 93.20% recognition rate. � 2013 IEEE.
- «
- 1 (current)
- 2
- 3
- »