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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Okade, Manish Biswas, Prabir Kumar BVB Coll Engn & Technol Dept Elect & Commun Engn Hubli India Indian Inst Technol Dept Elect & Elect Commun Engn Kharagpur 721302 W Bengal India

ISBN: (纸本)9781479915880

this paper investigates a novel motion vector outlier rejection method based on using mean shift clustering on block motion vectors. the accuracy of compressed domain global motion estimation techniques is largely influenced by its ability to counter the outlier motion vectors. these outliers occur in the block motion vector field due to moving objects, noise or due to large matching errors as a result of the encoders priority on rate distortion optimization. In the present work it is shown that by using mean shift clustering on block motion vectors, those clusters which correspond to outlier motion vectors can be identified. Once detected these clusters are kept out of the global motion estimation process thereby increasing the robustness of estimated camera parameters. the proposed method is compared with existing state-of-the-art outlier removal methods using synthetic and real video sequences to establish and validate its superiority.

关键词： outlier motion vectors mean shift clustering global motion estimation compressed domain

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Cross-modal Attribute Based Facial image Retrieval 5

Cross-modal Attribute Based Facial Image Retrieval

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Mali, Dasharath Biswas, Soma Indian Inst Sci Dept Elect Engn Bangalore Karnataka India

ISBN: (纸本)9781467385640

Attribute-based facial image retrieval has wide range of applications, such as in law enforcement, online social networks, etc. the problem becomes more challenging if the images are from different modalities. For example, the input is a sketch or a composite image, and the task is to retrieve photo images which have the same facial attributes as the input data. In this work, we propose a learning-based approach, in which two transformations are learnt to transform the training images from the two modalities with associated attribute annotations such that images which have similar attributes move closer to each other, and images with very different attributes move farther from each other in the transformed space. Given a query image, it is first transformed to the learnt space in which the images with similar attributes are retrieved. the same framework works seamlessly if the images to be retrieved are of same or different modality as compared to the query data. the attributes of the query image are also automatically obtained as a byproduct of the algorithm. Extensive experimental evaluation on three datasets shows the effectiveness of the proposed approach.

关键词： image retrieval

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Recognizing Newborns using Binocular Region 5

Recognizing Newborns using Binocular Region

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Parmar, Chandani Vishwamitra, L. K. Patel Coll Sci & Technol Dept Comp Sci & Engn Bhopal India

ISBN: (纸本)9781467385640

Existing approaches on newborn identification focuses on recognizing them using face, inked footprints, and palm prints. While palm and inked footprints are intrusive modalities, face modality suffers from non-cooperative nature of newborns. In this research, we investigate utilization of binocular region for recognizing newborns, as this region is considered to be relatively stable in face biometrics literature. We collect a database consisting of 402 face images pertaining to 50 babies of less than 6 months of age. A set of experiments pertaining to various descriptors, including local binary patterns, dense scale invariant feature transform, and Gabor features, along with subspace learning using principal component analysis, linear discriminant analysis, and independent component analysis. Recognition performance of various approaches are compared with respect to face and binocular modalities. Verification results are reported in terms of Receiver operating characteristics curves respectively. the results show that binocular can outperform face as a modality for newborn recognition.

关键词： Principal component analysis

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An image Encryption Algorithm based on XOR Operation with Approximation Component in Wavelet Transform 5

An Image Encryption Algorithm based on XOR Operation with Ap...

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Singh, Piyush Kumar Singh, Ravi Shankar Rai, Kabindra Nath Banaras Hindu Univ DST Ctr Interdisciplinary Math Sci Varanasi Uttar Pradesh India IIT BHU Dept Comp Sci & Engn Varanasi Uttar Pradesh India IIT BHU Dept Math Sci Varanasi Uttar Pradesh India

ISBN: (纸本)9781467385640

Wavelet transform of the image generates the different components basically classified in the approximation and detail components. the approximation component has major information. In this paper a partial encryption technique is used, using only approximation component. In this paper a random array is generated which is XORed with the approximation component. the inverse transform of the matrix generated by this operation generates the encrypted image. the random array, the wavelet used and level of wavelet transform jointly serves as the key for the decryption process. In decryption is just reverse of the encryption steps.

关键词： Wavelet Transform image Encryption XOR based Encryption Random Array based Encryption Decryption

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Looking to build a model world: Automatic construction of static object models using computer vision

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ELECTRONICS & COMMUNICATION ENGINEERING JOURNAL 1998年第3期10卷 103-113页

作者： Illingworth, J Hilton, A Univ Surrey Sch Elect Engn Informat Technol & Math Ctr Vis Speech & Signal Proc Guildford GU2 5XH Surrey England

Recent interest in virtual reality and multimedia has provided a great impetus to the development of automatic techniques for building graphical CAD/CAM models of objects and environments by sensing reality itself. the learning of models in this way is essential, particularly in terms of production times and attaining the required high fidelity needed for many applications Research has produced techniques for extracting full 3D shape models using a variety of sensors and a spectrum of techniques. these include the use of static video cameras, mobile video cameras (e.g. walk through video), multiple camera platforms and/or specialist active range sensors (typically based on laser striping or sonar). this paper introduces the principles and methodologies underlying several of these methods and presents algorithms and examples from systems representative of three major approaches: models from silhouettes, models from active range sensors and, finally, models from passive uncalibrated video sequences.

关键词： graphical CAD/CAM models walk through video video signal processing multiple camera platform 3D shape models static video cameras production times graphics techniques automatic construction computer vision silhouettes multimedia laser striping sonar mobile video cameras computer vision and image processing techniques virtual reality solid modelling static object models active range sensors model world passive uncalibrated video sequences image sequences

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Automatic Number Plate Recognition system using modified Stroke Width Transform

Automatic Number Plate Recognition system using modified Str...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Jobin, K. V. Jiji, C. V. Anurenjan, P. R. Coll Engn Trivandrum Trivandrum Kerala India

ISBN: (纸本)9781479915880

Automatic number plate recognition(ANPR) techniques occupy a significant role in intelligent traffic management systems. Most of the existing ANPR systems do not perform well under conditions like high vehicle speed, varying illuminations, changing back ground etc. In this paper we propose an ANPR technique which efficiently solves the above issues using the stroke width transform. In our method, first we pre-process the image to remove blurring artifacts. then the significant edges in the image are detected and a new image is formed by grouping the connecting rays. this is followed by morphological processing which detects the letters in the image. then an appropriate Optical Character Recognizer (OCR) recovers the final result. Experimental results show that the proposed method work effectively under varying light conditions and even in the presence of shadows.

关键词： Intelligent traffic management system License plates edge image morphological processing imagery (Psychotherapy) images Vehicle speed shadows letter recognition system image Transform Advanced traffic management systems(ATMS) passenger transportation management system Stroke

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Human Face Anthropometric Measurements Using Consumer Depth Camera 5

Human Face Anthropometric Measurements Using Consumer Depth ...

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Alavani, Gargi Kabirdas Kamat, Venkatesh Goa Univ DCST Taleigao Plateau Goa India

ISBN: (纸本)9781467385640

Human face anthropometric measurements are used in forensics, orthodontics, face modelling and many other domains, wherein distance between set of facial landmarks play an important role to make inferences. 3D facial data captured using specialized acquisition methods can be used to reduce the time and tedious task involved in order to compute these measurements. the proposed method is developed to compute fifteen canonical linear measurements between facial landmarks using Kinect camera. Results obtained from this system are compared with the traditional method of measurement using digital Vernier caliper. the experimental results indicate that measurements using RGB-D data obtained from Kinect are good enough for a quick preliminary assessment of the subject as compared to traditional method.

关键词： Cameras

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Fast, Processor-Cardinality Agnostic PRNG with a Tracking Application

Fast, Processor-Cardinality Agnostic PRNG with a Tracking Ap...

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6th indian conference on computer vision, graphics and image processing

作者： Janowczyk, Andrew Chandran, Sharat Aluru, Srinivas Indian Inst Technol Dept Comp Sci & Engn ViGIL Bombay 400076 Maharashtra India Iowa State Univ Sci & Technol Ames IA 50011 USA

ISBN: (纸本)9781424442195

As vision algorithms mature with increasing inspiration from the learning community, statistically independent pseudo random number generation (PRNG) becomes increasingly important. At the same time, execution time demands have seen algorithms being implemented on evolving parallel hardware such as GPUs. the Mersenne Twister (MT) [7] has proven to be the current state of the art for generating high quality random numbers, and the Nvidia provided software for parallel MT is in widespread use. While execution time is important, development time is also critical. As processor cardinality changes, a foundation for generating simulations that will vary only in execution time and not in the actual result is useful;otherwise the development time will be impacted. In this paper we present an implementation of the Lagged Fibonacci Generator (LFG) considered to be of quality equal [7] to MT on the GPU. Unlike MT LFG has this important processor-cardinality agnostic capability that is - as the number of processing resources changes, the overall sequence of random numbers remains the same. this feature notwithstanding, our basic implementation is roughly as fast as the parallel MT;an in-memory version is actually 25% faster in execution time. Both parallel MT as well as parallel LFG show enormous speedup over their sequential counterparts. Finally, a prototype particle filter tracking application shows that our method works not just in parallel computing theory, but also in practice for vision applications, providing a decrease of 60% in execution time.

关键词： Program processors

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RST Invariant Multi View 3D image Watermarking Using DWT and SVD 5

RST Invariant Multi View 3D Image Watermarking Using DWT and...

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Gaj, Sibaji Rana, Shuvendu Lekharu, Anirban Sur, Arijit Bora, Prabin Kumar Indian Inst Technol Dept CSE Multimedia Lab Gauhati 781039 Assam India Indian Inst Technol Dept EEE Gauhati 781039 Assam India

ISBN: (纸本)9781467385640

In this paper, a multi-view stereo image watermarking scheme is proposed to resist the RST (rotation, scaling and translation) attack. To make the scheme resilient to RST, the coefficients of Singular Value Decomposition (SVD) from both left and right views have been used for insertion of the watermark bits. 2D-DWT (Discrete wavelet transform) is used as a preprocessing step to get more correlated SVD coefficients of the left and right view such that the visual degradation due to embedding can be reduced. In this work, a blind embedding scheme is proposed by altering the selected SVD coefficients to improve the robustness of the embedding scheme. A comprehensive set of experiments have been performed to justify the robustness of the proposed scheme against RST attack. Moreover, this scheme can be used to detect the view swapping attack using DIBR technique.

关键词： Singular value decomposition

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Spatial Variance of Color and Boundary Statistics for Salient Object Detection

Spatial Variance of Color and Boundary Statistics for Salien...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Roy, Sudeshna Das, Sukhendu Indian Inst Technol Dept Comp Sci & Engn Visualizat & Percept Lab Madras 600036 Tamil Nadu India

ISBN: (纸本)9781479915880

Bottom-up saliency detection algorithms identify distinct regions in an image, with rare occurrence of local feature distributions. Notable among those works published recently, use local and global contrast, spectral analysis of the entire image or graph based feature mapping. Whereas, we propose a novel unsupervised method using color compactness and statistical modeling of the background cues, to segment the salient foreground region and thus the salient object. At the first stage of processing, the image is segmented into clusters using color feature. First component proposed for our saliency measure combines disparity in color and spatial distance between patches. In addition to rarity of feature, we propose another component for saliency computation that estimates the divergence of the color of a patch from those in the set of patches at the boundary of the image, representing the background. Combination of these two complementary components provides a much improved saliency map for salient object detection. We verify the performance of our proposed method of saliency detection on two popular benchmark datasets, with one or more salient regions and diverse saliency characteristics. Experimental results show that our method outperforms many existing state-of-the-art methods.

关键词： Object detection Color images imagery (Psychotherapy) color feature image boundary layer statistical models (nuclear) Patches Boundary

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