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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Renu Sharma Sukhendu Das Padmaja Joshi Centre for Development of Advanced Computing Mumbai Indian Institute of Technology Madras

Multibiometric systems have recently become a preferred option for human identification over the unibiometric systems. It increases the recognition rate and confidence in the final decision, and simultaneously reduces the failure to enroll rate (FER). For identification mode, rank level fusion is a feasible option as incompatibility and normalization issues present at the score level fusion are not prominent at this level and also sufficient information is present to fuse as opposed to the decision level fusion. We propose an improvement in existing rank level fusion techniques using two levels of hierarchy. Series and parallel combinations are proposed to combine the output of various rank level fusion techniques. Two formulations of series and parallel combinations are extensively evaluated on multi-algorithm, multi-instance and multi-modal biometric systems created from three publicly available datasets: (i) NIST BSSR1 [1] multi-modal biometric score database, (ii) Face Recognition Grand Challenge V2.0 [2] and (iii) LG4000 [3] iris images.

关键词： Face Iris recognition Face recognition NIST Training Fingerprint recognition

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A hierarchical class-grouping approach, and a study of classification strategies for leaf classification

A hierarchical class-grouping approach, and a study of class...

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Ravinder Prajapati Arnav Bhavsar Anil Sao School of Computing and Elec. Engg. Indian Institute of Technology Mandi

Fine-grained visual classification has been considered for image data in various domains of environmental importance such as birds, animals and plants. This work considers the classification problem of the latter, based on the leaf shape. Traditional works in such areas typically propose better features, or sophisticated classification frameworks. In this work, we ask a different question: Given simple and efficient features, and a well-known binary classifier such as support vector machine (SVM), among various strategies, what may be a good way to pose the multi-class classification problem as multiple binary classifications? In this respect, we compare three different strategies, all of which use the same set of features. From our results, we conclude that, one of these three approaches, based on hierarchical class-grouping, clearly outperforms the others, with high classification accuracy. This suggest that classification strategy is an important aspect for the given features and classifiers. To our knowledge, such a study in the fine-grained classification area (and particularly for the nascent area of leaf-classification), has not yet been explored.

关键词： Shape Support vector machines Feature extraction Visualization image color analysis Veins Libraries

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Pose and illumination invariant face recognition using binocular stereo 3D reconstruction

Pose and illumination invariant face recognition using binoc...

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Aditya Nigam Gitesh Chhalotre Phalguni Gupta School of Computing and Electrical Engineering Indian Institute of Technology Mandi India Department of CSE Indian Institute of Technology Kanpur India CSE Department NITTTR Salt Lake India

Traditional 2D face recognition systems drastically fails with pose variance and poor illuminations. Many techniques but with limited success has been introduced. Expensive 3D setup can be used to deal with this problem. In this work a low cost, low computation and quick good quality 3D reconstruction helping 2D face recognition systems is proposed. The proposed system is a fast automatic 3D face reconstruction approach from rectified stereo images. An automatic synthesis of training images of various face poses is proposed. Three enhancements adaptive histogram equalization (AHE) to improve contrast of face images, horizontal gradient ordinal relationship pattern(HGORP) to handle poor illumination and steerable filter(SF) for noise reduction and illumination invariance are used to improve the system performance. Later SURF based matching is done with score level fusion of all three enhancements. A database of 107 subjects has been collected to evaluate the system performance. It is observed that the proposed system can handle large pose variations and poor illumination very well.

关键词： Face Three-dimensional displays Face recognition Lighting Solid modeling image reconstruction Computational modeling

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PD-Shift: Patch Detector Shift based Tracker

PD-Shift: Patch Detector Shift based Tracker

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Mathew Francis Ratnakaram Rajesh Prithwijit Guha Dept. of EEE IIT Guwahati Indian Institute of Technology Guwahati Guwahati Assam IN

We identify two important directions of algorithm development in the tracking literature - first, the older and more established mean-shift based approaches; and second, more recent formulations of viewing tracking as detection by parts (aka tracking-learning-detecting). Introductory versions of both these approaches had their own weaknesses due to the main challenges of tracking like illumination variations, abrupt motions, deformations/articulations and occlusions. Both these approaches have developed independently with a number of follow-ups in the literature and even the matured versions were never integrated. We propose to integrate these two different viewpoints of single object tracking where the contribution lies in the construction of the target model as a collection of object part/patch detectors integrated with a kernel. Similarly, the kernel weighted patch detector responses form the candidate model. The Bhattacharyya coefficient based similarity measure between the target and candidate model is maximized in a gradient ascent framework to deduce a mean-shift like centroid update rule to iteratively track the target in the subsequent frames. We call this unified one the Patch Detector Shift based Tracker (PD-Shift). Experimental results of PD-Shift based tracking performance analysis is presented for the BoBoT dataset.

关键词： Detectors Kernel Target tracking Object tracking image color analysis computer vision Robustness

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Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2016年 10481 LNCS卷 V页

作者： Mukherjee, Snehasis Mukherjee, Suvadip Mukherjee, Dipti Prasad Sivaswamy, Jayanthi Awate, Suyash Setlur, Srirangaraj Namboodiri, Anoop M. Chaudhury, Santanu Indian Institute of Information Technology SriCity India Indian Institute of Technology Bombay Mumbai India GE Global Research Bangalore India CEDAR BuffaloNY United States Indian Statistical Institute Kolkata India International Institute of Information Technology Hyderabad India CSIR-CEERI Pilani Rajasthan India

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Complexity assisted consistent quality rate control for high resolution H.264 video conferencing

Complexity assisted consistent quality rate control for high...

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Subhomoy Bhattacharyya Indrajit Chakrabarti Maheshkumar H. Kolekar Squid Systems Inc. Hyderabad Indian Institute of Technology Kharagpur Kharagpur Indian Institute of Technology Patna Patna

Video based multimedia services are showing major growth in recent years. Though the video coding recommendation ITU-T H.265/HEVC is in operating state, the majority of real-time video applications including video conferencing and live streaming of events rely mainly on less computationally intensive H.264/AVC coding standard which is well established among video industry. Rate control algorithms are indispensable for delivering superior quality video over limited bandwidth connections. In this paper, we propose a rate control technique which provides consistent quality video output over time in a limited bandwidth video conferencing scenario. Using the concept of video traffic prediction and linear complexity model, we compute the complexity of the video sequence in real time. We present a better estimate of quantization parameter at the GOP (group of picture) layer. Our proposed method maintains similar quality for reconstructed video when compared to rate control scheme of JM 19.0 implemented in real-time video conferencing system with restricted quality variation. On an average, 22% improvement has been observed in terms of standard deviation of frame PSNR values when compared to JM 19.0 rate control scheme implemented in high resolution video conferencing scenario.

关键词： Streaming media Complexity theory Encoding Real-time systems Standards Bandwidth Predictive models

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Automated conversion of 2D to 3D image using manifold learning

Automated conversion of 2D to 3D image using manifold learni...

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Nidhi Chahal Meghna Pippal Santanu Chaudhury Department of Electrical Engineering Indian Institute of Technology Delhi India

Automatic technique of 2D to 3D image conversion is proposed using manifold learning and sequential labeling which generates very reliable and accurate 3D depth maps that are very close to ground truth depths. In paper, LLE which is a non linear and neighborhood preserving embedding algorithm is used for depth estimation of a 2D image. And then, fixed point supervised learning algorithm is applied to construct consistent and smooth 3D output. The high dimensional data points or pixels of the input frames can be represented by a linear combination of its nearest neighbors and a lower dimensional point is reconstructed while preserving the local and geometric properties of the frames. The neighbors are assigned to each input point in the image data set and their weight vectors are computed that best linearly reconstruct the input point from its neighbors. To get the depth value of input point in new image, the reconstruction weights of its closest neighbors in training samples are multiplied with their corresponding ground truth depth values. The fixed point learning algorithm takes depths from manifold and other image features as input vectors and generates more consistent and accurate depth images for better 3D conversion.

关键词： Manifolds Three-dimensional displays image reconstruction Estimation Supervised learning image color analysis image edge detection

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A low complexity block matching algorithm for fast motion estimation in High Efficiency Video Coding

A low complexity block matching algorithm for fast motion es...

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： K.C. Ravi Chandra Varma Venkata Phani Kumar M. Sudipta Mahapatra Electronics and Electrical Communication Engineering Indian Institute of Technology Kharagpur Kharagpur West Bengal IN Electronics and Electrical Communication Engineering IIT Kharagpur West Bengal India

This paper proposes a search mechanism, namely accelerated internal stop search (AISS), to reduce the complexity of the block matching process used for motion estimation in High Efficiency Video Coding (HEVC). The proposed mechanism reduces the number of operations required to find the best matching reference block. Moreover, it uses the correlation with the previous reference frames to further reduce the complexity of motion estimation for the current reference frame. Results demonstrate that the proposed mechanism is able to reduce the complexity of motion estimation in the fast search mode of the HM-14.0 reference software for HEVC, i.e., the TZ Search motion estimation. The AISS mechanism outperforms the dynamic internal stop search algorithm (DISS) proposed by Ismail et al. in the year 2012 in terms of motion estimation time saving. Moreover, when AISS is integrated with the dynamic model based fast motion estimation proposed by Ismail et al. [1], the complexity of motion estimation is further reduced.

关键词： Complexity theory Motion estimation Mathematical model Heuristic algorithms Bit rate Video recording Quality assessment

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Study of variation of pelvis positioning for patients suffering from rectal cancer using daily kilo-voltage cone beam CT images

Study of variation of pelvis positioning for patients suffer...

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Sayan Mandal Bijju Kranthi Veduruparthi Jayanta Mukherjee Partha Pratim Das Indranil Mallick Department of Computer Science and Engineering Indian Institute of Technology Kharagpur Department of Radiation Oncology Tata Medical Center Kolkata

ISBN: (纸本)9781467385657

Radiation therapy is a standard treatment for a large variety of cancers. Radiation treatment planning involves delineating tumor, areas-at-risk, as well as normal anatomical structures. Automated techniques for detection and segmentation of tumor is a challenging task because of the absence of any standard model to identify anatomical structures. As radiation therapy is delivered in multiple daily doses (called fractions) - treatment fields need to be positioned so that the daily uncertainties in the target position are covered adequately. This is done by adding a margin called the Planning Target Volume (PTV) margin around the clinical target volume. The PTV margin is determined from an understanding of the daily uncertainties. In this paper, we intend to aid doctors in determining the uncertainties of daily pelvis positioning for radiotherapy by estimating the degree of change in the pelvic bone position. We propose a technique for automatically detecting regions of pelvic bone anatomy from CBCT images. We track the change in the bone positions in pelvic regions on a daily basis. A small change suggests that the uncertainty involved in the position of tumorous cell is less, indicating that the planning target margin may be reduced substantially.

关键词： Planning Computed tomography Pelvic bones Tumors Shape Correlation

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Writer Identification from offline isolated Bangla characters and numerals 13

Writer Identification from offline isolated Bangla character...

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13th International conference on Document Analysis and Recognition, ICDAR 2015

作者： Adak, Chandranath Chaudhuri, Bidyut B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata700108 India

ISBN: (纸本)9781479918058

Writer identification is an essential component in computational forensic. In this paper, we attempt to do this job based only on isolated characters and numerals. For that, at first, some points of interest (keypoints) on the image are detected by structural analysis and SIFT based detector. Then we calculate a set of features within a certain neighborhood of the keypoint and employ fusion rule on multiple probabilistic SVM classifiers output for writer identification. For experimental analysis, a database containing 212,300 isolated Bangla orthosyllabic characters and numerals are generated with the help of 100 writers. We obtain fairly good result to identify a writer. We also try to find a small set of highly discriminative characters storing extra information about the writing style of an individual. © 2015 IEEE.

关键词： handwriting recognition natural language processing probability support vector machines Bangla orthosyllabic characters SIFT based detector computational forensic isolated Bangla characters isolated Bangla numerals isolated characters multiple probabilistic SVM classifiers structural analysis writer identification Chlorine Discriminative Bangla character Handwriting analysis Writer identification Numerals handwriting recognition structural analysis Structural analysis Support Vector Network Natural Language processing Writers Chlorine

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