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Recursive structure from motion 10

Recursive structure from motion

引用

10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Chebiyyam, M. Chaudhury, S. Kar, I.N. Department of Electrical Engeneering Indian Institute of Technology Delhi New Delhi India

In this paper we present a technique that estimates the Structure from Motion (SFM) in a recursive fashion. Traditionally successful SFM algorithms take the set of images and estimate the scene geometry and camera positions either using incremental algorithms or the global algorithms and do the refinement process [2] to reduce the reprojection error. In this work it is assumed that we don’t have complete image set at the start of the reconstruction process, unlike most of the traditional approaches present in the literature. It is assumed that the set of images come in at the regular intervals and we recursively perform the SFM on the incoming set of images and update the previously reconstructed structure with the structure estimated from the current set of images. the proposed system has been tested on two datasets which consist of 12 images and 60 images respectively and reconstructions obtained show the validity of our proposed technique. © Springer International Publishing AG 2017.

关键词： image reconstruction

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A text recognition augmented deep learning approach for logo identification 10

A text recognition augmented deep learning approach for logo...

引用

10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Medhi, Moushumi Sinha, Shubham Sahay, Rajiv Ranjan Computational Vision Lab Department of Computer Science and Engineering Indian Institute of Technology Kharagpur KharagpurWest Bengal721302 India Department of Computer Science and Technology Indian Institute of Engineering Science and Technology ShibpurWest Bengal711103 India Department of Electrical Engineering Indian Institute of Technology Kharagpur KharagpurWest Bengal721302 India

Logo/brand name detection and recognition in unstructured and highly unpredictable natural images has always been a challenging problem. We notice that in most natural images logos are accompanied with associated text. therefore, we address the problem of logo recognition by first detecting and isolating text of varying color, font size and orientation in the input image using affine invariant maximally stable extremal regions (MSERs). Using an off-the-shelf OCR, we identify the text associated with the logo image. then an effective grouping technique is employed to combine the remaining stable regions based on spatial proximity of MSERs. Deep learning has the advantage that optimal features can be learned automatically from image pixel data. this motivates us to feed the clustered logo candidate image regions to a pre-trained deep convolutional neural network (DCNN) to generate a set of complex features which are further input to a multiclass support vector machine (SVM) for classification. We tested our proposed logo recognition system on 32 logo classes, and a non-logo class obtained by combining FlickrLogos-32 and MICC logo databases, amounting to a total of 23582 training and testing images. Our method yields robust recognition performance, outperforming state-of-the-art techniques achieving 97.8% precision, 95.7% recall and 95.7% average accuracy on the combined MICC and FlickrLogos-32 datasets and a precision of 98.6%, recall of 97.9% and average accuracy of 99.6% on only the FlickrLogos-32 dataset. © Springer International Publishing AG 2017.

关键词： Deep neural networks

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A beta distribution based novel scheme for detection of changes in crowd motion 10

A beta distribution based novel scheme for detection of chan...

引用

10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Pal, Soumyajit Mondal, Sounak Saha, Sanjoy Kumar Chanda, Bhabatosh Department of Computer Science and Engineering Jadavpur University Kolkata India Electronics and Communication Sciences Unit Indian Statistical Institute Kolkata India

An automated system for crowd behaviour analysis has gained significance in the context of surveillance and public management. Detecting the changes in the crowd behaviour demarcates one activity or event from another. thus, change detection is a fundamental step that enables the subsequent characterisation of the activities and analysis of the transition from one state to another. Proposed work deals with high density crowd. Global motion is an important cue for studying the behaviour of such crowd. In this work, crowd motion is modelled using beta distribution. Change in the distribution parameter is an indicator for change in crowd motion pattern. Proposed methodology has been tested with number of synthetic and natural video sequences and the performance is satisfactory. © Springer International Publishing AG 2017.

关键词： Automation

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A novel intelligent multiple watermarking schemes for the protection of the information content of a document image 10

A novel intelligent multiple watermarking schemes for the pr...

引用

10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Chetan, K.R. Nirmala, S. Department of CSE JNN College of Engineering ShimogaKarnataka India

Most of the past document image watermarking schemes focus on providing same level of integrity and copyright protection for information present in the source document image. However, in a document image the information contents possess various levels of sensitivity. Each level of sensitivity needs different type of protection and this demands multiple watermarking techniques. In this paper, a novel intelligent multiple watermarking techniques are proposed. the sensitivity of the information content of a block is based on the homogeneity and relative energy contribution parameters. Appropriate watermarking scheme is applied based on sensitivity classification of the block. Experiments are conducted exhaustively on documents. Experimental results reveal the accurate identification of the sensitivity of information content in the block. the results reveal that multiple watermarking schemes has reduced the amount of data to be embedded and consequently improved perceptual quality of the watermarked image. © Springer International Publishing AG 2017.

关键词： image watermarking

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Neovascularization detection on retinal images 10

Neovascularization detection on retinal images

引用

10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Kar, Sudeshna Sil Maity, Santi P. Maity, Seba Department of Information Technology Indian Institute of Engineering Science and Technology Shibpur Howrah711103 India Department of Electronics and Telecommunication Engineering College of Engineering and Management Kolaghat Kolaghat India

Proliferative Diabetic Retinopathy (PDR) is characterized by the growth of new abnormal, thin blood vessels called neovascu-larzation that spread along the retinal surface. An automated computer aided diagnosis system needs to identify neovasculars for PDR screening. Retinal images are often noisy and poorly illuminated. the thin vessels mostly appear to be disconnected and are inseparable from the background. this paper proposes a new method for neovascularization detection on retinal images. Blood vessels are extracted as thick, medium and thin types using multilevel thresholding on matched filter response. the total mutual information between the vessel density and the tortuosity of the thin vessel class is maximized to obtain the optimal thresholds to classify the normal and the abnormal vessels. Simulation results demonstrate that the proposed method outperforms the existing ones for neovascularization detection with an average accuracy of 97.54%. © Springer International Publishing AG 2017.

关键词： Blood vessels

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Dictionary based approach for facial expression recognition from static images 10

Dictionary based approach for facial expression recognition ...

引用

10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Sharma, Krishan Rameshan, Renu School of Computing and Electrical Engineering Indian Institute of Technology MandiHimachal Pradesh India

We present a simple approach for facial expression recognition from images using the principle of sparse representation using a learned dictionary. Visual appearance based feature descriptors like histogram of oriented gradients (HOG), local binary patterns (LBP) and eigenfaces are used. We use Fisher discrimination dictionary which has discrimination capability in addition to being reconstructive. the classification is based on the fact that each expression class with in the dictionary spans a subspace and these subspaces have non-overlapping directions so that they are widely separated. Each test feature point has a sparse representation in the union of subspaces of dictionary formed by labeled training points. To check recognition performance of the proposed approach, extensive experimentation is done over Jaffee and CK databases. Results show that the proposed approach has better classification accuracy than state-of-the-art techniques. © Springer International Publishing AG 2017.

关键词： Local binary pattern

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vision based pose estimation of multiple peg-in-hole for robotic assembly 10

Vision based pose estimation of multiple peg-in-hole for rob...

引用

10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Nagarajan, Pitchandi Perumaal, S. Saravana Yogameena, B. Department of Mechanical Engineering Thiagarajar College of Engineering Madurai625015 India Department of Electronics and Communication Engineering Thiagarajar College of Engineering Madurai625015 India

vision sensors are used to estimate the pose (position and orienta-tion) of mating components in a vision assisted robotic peg-in-hole assembly which is a crucial step in aligning the mating hole-component with the corresponding moving peg-component. the accuracy of this estimation decides the performance of peg-in-hole robotic assembly with an appropriate mapping between the image and task environment using a fixed overhead camera or camera on robot arm. the wheel and hub assembly in automobile has multiple holes and pegs in their mating parts which lead to more complex pose estimation procedure. the success rate of the assembly process (without jamming) is affected by an inaccurate pose estimation which leads to lateral and/or axial misalignment between the mating components during its insertion phase. On this consideration, this work proposes a pose estimation algorithm for a multiple peg-in-hole assembly with the use of genetic algorithm based two-stage camera calibration procedure. the proposed algorithm has also been tested for its performance in estimating the pose of the multiple pegs in wheel-hub of a car. the result reveals that the proposed method estimates the pose of the pegs accurately with minimum re-projection error. © Springer International Publishing AG 2017.

关键词： Genetic algorithms

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Text and non-text separation in scanned color-official documents 10

Text and non-text separation in scanned color-official docum...

引用

10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Nandedkar, Amit Vijay Mukherjee, Jayanta Sural, Shamik Department of Computer Science and Engineering Indian Institute of Technology Kharagpur Kharagpur India

Official documents consist of text and non-textual elements such as logo, stamp, and signature. Separation of these elements from a scanned document plays a significant role in document image retrieval, recognition, and verification. this paper presents a novel scheme to separate text and non-text elements of official documents using part-based features. In this work, we exploit the fact that intensity distributions of text and non-text elements in HSV color space are of distinctive nature. A new approach to compute part-based features using S and V channels is proposed. the classification of text and non-text components is performed based on majority voting scheme and K-approximate nearest neighbors. the knowledge base acquired during training is indexed using kD-tree indexing scheme. Subsequently, the method is extended for detection of logo, stamp, and signature. Experimental results show the effectiveness of the proposed approach. © Springer International Publishing AG 2017.

关键词： Nearest neighbor search

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Distribution based EEG baseline classification 10

Distribution based EEG baseline classification

引用

10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Gopika Gopan, K. Sinha, Neelam Dinesh Babu, J. International Institute of Information Technology Bangalore Bangalore India

Electrical signals generated in the brain, known as Electroen-cephalographic (EEG) signals, form a non-invasive measure of brain functioning. Baseline states of EEG are Eyes Open (EO) and Eyes Closed (EC) relaxed states. the choice of baseline used in an experiment is of critical importance since they form a reference with which other states are measured. In Brain Machine Interface, it is imperative that the system should be able to distinguish between these states and hence the need for automated classification of EEG baselines. In the proposed method, Statistical Moments are utilized. the Moment Generating Functions (MGFs) obtained using these moments are given as features to SVM and k-NN classifiers resulting in mean accuracies of 86.71% and 86.54%. the fact that MGF is able to differentiate between these states indicate that the two states have different source distribution parameters. A Smirnov test verified that the data of two classes indeed come from different distributions. © Springer International Publishing AG 2017.

关键词： Brain computer interface

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Brain tumor segmentation from multimodal MR images using rough sets 10

Brain tumor segmentation from multimodal MR images using rou...

引用

10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Saha, Rupsa Phophalia, Ashish Mitra, Suman K. Dhirubhai Ambani Institute of Information and Communication Technology GandhinagarGujarat382007 India Indian Institute of Information Technology Vadodara GandhinagarGujarat382028 India

Automatic segmentation of brain tumors from Magnetic Resonance images is a challenging task due to the wide variation in intensity, size, location of tumors in images. Defining a precise boundary for a tumor is essential for diagnosis and treatment of patients. Rough set theory, an extension of classical set theory, deals with the vagueness of data by determining the boundary region of a set. the aim of this work is to explore the possibility and effectiveness of using a rough set model to represent the tumor regions in MR images accurately, with Quadtree partitioning and simple K-means as precursors to indicate and limit the possible relevant regions. the advantage of using rough sets lie in its ability to represent the impreciseness of set boundaries, which is one of the major challenges faced in tumor segmentation. Experiments are carried out on the BRATS 2013 and 2015 databases and results are comparable to those reported by recent works. © Springer International Publishing AG 2017.

关键词： Magnetic resonance imaging

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