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11th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Alex, Doney Sami, Zishan Banerjee, Sumandeep Panda, Subrat Capillary Technol Bengaluru India Indian Inst Technol Kharagpur Kharagpur W Bengal India

ISBN: (纸本)9781450366151

Person re-identification (ReID) is an important problem in computer vision, especially for video surveillance applications. The problem focuses on identifying people across different cameras or across different frames of same camera. The main challenge lies in identifying similarity of the same person against large appearance and structure variations, while differentiating between individuals. Recently, deep learning networks with triplet loss has become a common framework for person ReID. However, triplet loss focuses on obtaining correct orders on the training set. We demonstrate that it performs inferior in a clustering task. In this paper, we design a cluster loss, which can lead to the model output with a larger interclass variation and a smaller intra-class variation compared to the triplet loss. As a result, our model has a better generalisation ability and can achieve a higher accuracy on the test set especially for a clustering task. We also introduce a batch hard training mechanism for improving the results and faster convergence of training.

关键词： Cameras

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CBP and ART image reconstruction algorithms on media and DSP processors

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MICROPROCESSORS AND MICROSYSTEMS 2001年第5期25卷 233-238页

作者： Rajan, K Patnaik, LM Indian Inst Sci Dept Phys Bangalore 560012 Karnataka India Indian Inst Sci Microprocessor Applicat Lab Bangalore 560012 Karnataka India

Computed Tomography (CT) image reconstruction algorithms such as convolution back-projection (CBP) and algebraic reconstruction technique (ART) are highly compute-intensive for today's single processor systems. In this work, we investigate the suitability of TM-1000 media processor and Analog Device's ADSP 21160 as a compute engine for the execution of image reconstruction algorithms. Philips Trimedia TM-1000, a very large instruction word (VLIW) processor, is a high performance media processor optimized for realtime processing of audio, video, graphics, and communication data streams. TM-1000 has a high performance digital signal processor (DSP) core, supported by multiple functional units. The DSP core and the functional blocks operate in parallel, driven by a mix of RISC, multimedia, SIMD-type DSP and floating point instructions. A typical DSP such as Analog Device's ADSP 21160 is based on super harvard architecture (SHARC) and is an optimized processor for digital signal processing applications. It has two sets of computation units. Each p computation unit comprises of three functional blocks namely, arithmetic and logic unit (ALU), multiplier and shifter unit. ADSP 21160 supports single instruction multiple data (SIMD) computation model to handle dual computation units. Both sets of computation units operate concurrently. We compare the performance of TM-1000 media processor and ADSP 21160 DSP processor to execute the image reconstruction algorithms by comparing the execution time of CBP and ART algorithms on them. The image reconstruction algorithms normally break down to a repetitive multiply-accumulate operation (MAC). All DSP processors support single-cycle MAC and zero-overhead loop instructions. The media processors normally do not support single-cycle MAC instruction and zero-overhead loop functionality. However, media processors are equipped with multiple functional units that perform multiple operations in a single instruction time. A DSP processor is

关键词： DSP computerized tomography back-projection

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A Distribution-Independent Risk Estimator for image Denoising 16

A Distribution-Independent Risk Estimator for Image Denoisin...

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

作者： Subramanian, Babu Kishore Gupta, Ashutosh Seelamantula, Chandra Sekhar Sattva MedTech Bangalore 560025 Karnataka India Indian Space Res Org Ahmadabad 380015 Gujarat India Indian Inst Sci Bangalore 560012 Karnataka India

ISBN: (纸本)9781450347532

We address the problem of image denoising for an additive white noise model without placing any restrictions on the statistical distribution of noise. We assume knowledge of only the first-and second-order noise statistics. In the recent mean-square error (MSE) minimization approaches for image denoising, one considers a particular noise distribution and derives an expression for the unbiased risk estimate of the MSE. For additive white Gaussian noise, an unbiased estimate of the MSE is Stein's unbiased risk estimate (SURE), which relies on Stein's lemma. We derive an unbiased risk estimate without using Stein's lemma or its counterparts for additive white noise model irrespective of the noise distribution. We refer to the MSE estimate as the generic risk estimate (GenRE). We demonstrate the effectiveness of GenRE using shrinkage in the undecimated Haar wavelet transform domain as the denoising function. The estimated peak-signal-to-noise-ratio (PSNR) using GenRE is typically within 1% of the PSNR obtained when optimizing with the oracle MSE. The performance of the proposed method is on par with SURE for Gaussian noise distribution, and better than SURE-based methods for other noise distributions such as uniform and Laplacian distribution in terms of both PSNR and structural similarity (SSIM).

关键词： Risk estimation undecimated wavelet transform image denoising wavelet shrinkage generic risk estimation (GenRE)

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Design and Development of 3-D Urban Geographical Information Retrieval Application Employing Only Open Source Instruments

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1st International conference on computer vision and image processing (CVIP)

作者： Khan, Ajaze Parvez Porwal, Sudhir Khare, Sangeeta Minist Def DEAL DRDO Dehra Dun Uttar Pradesh India

ISBN: (纸本)9789811021046;9789811021039

Numerous 3-D GIS are being developed today that are both commercially and freely available. A multicity web-based 3-D GIS (named as GLC3d) using open source and freely available software/packages exclusively has been developed. This paper presents the architecture, design, and overview of GLC3d. Open source tools and software's QGIS, Cesium, and MySQL are employed to develop this application. QGIS is utilized for data preparation such as raster, vector, and subsidiary data. MySQL is utilized as database store and data population. GLC3d is based on Cesium (a JavaScript library for creating 3-D globes and 2-D maps in a web browser) and WebGL (a JavaScript API for rendering interactive 3-D computer graphics and 2-D graphics) to display 3-D Globe on the web browser. 3-D visualization for the urban/city geodata is presented on an interactive 3-D Globe. Various city information are generated and incorporated in to the 3-D WebGIS for data representation and decision making.

关键词： GIS (Geographical Information System) WebGL (Web graphics Library) Cesium MySQL KML (Key Hole markup Language) GeoJSON WMS (Web Map Service) OGC (Open Geospatial Consortium) DTM (Digital Terrain Model)

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An effficient hybrid fingerprint matching algorithm

An effficient hybrid fingerprint matching algorithm

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2011 3rd National conference on computer vision, Pattern Recognition, image processing and graphics, NCVPRIPG 2011

作者： Das, Priyanka Karthik, Kannan Chandra Garai, Boul Electronics and Electrical Engineering Dept. Indian Institute of Technology Guwahati Guwahati Assam 781039 India ISRO Satellite Centre Bangalore India

ISBN: (纸本)9780769545998

In this paper, a hybrid fingerprint matching algorithm based on phase correlation and minutiae points is proposed to improve the matching accuracy in fingerprint verification system. The phase correlation function which operates in the Fourier domain is used to determine the rotational offset while the core point detection algorithm is used to provide translational adjustment. Finally to match the aligned input and template minutiae sets, a Weighted Average Distance (WAD) measure is introduced. Experimental results show that the proposed method has an Equal Error Rate of 1.02% and 0.77% on two public domain databases FVC2002-DB1a and FVC2002-DB2a respectively. © 2011 IEEE.

关键词： Pattern matching

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Quantization Based Data Hiding Scheme for Efficient Quality Access Control of images using DWT via Lifting

Quantization Based Data Hiding Scheme for Efficient Quality ...

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

作者： Phadikar, Amit Maity, Santi P. Kundu, Malay K. MCKV Inst Engn Dept Informat Technol Liluah 711204 Howrah India Bengal Engn & Sci Univ Dept Informat Technol Howrah 711103 India Indian Stat Inst Mach Intelligence Unit & Ctr Soft Comp Kolkata 700108 India

ISBN: (纸本)9781424442195

This paper proposes a transform domain data-hiding scheme for quality access control of images. The original image is decomposed into tiles by applying n-level lifting-based Discrete Wavelet Transformation (DWT). A binary watermark image (external information) is spatially dispersed using the sequence of number generated by a secret key. The encoded watermark bits are then embedded into all DWT-coefficients of n(th)-level and only in the high-high (HH) coefficients of the subsequent levels using dither modulation (DM) but without complete self-noise suppression. It is well known that due to insertion of external information, there will be degradation in visual quality of the host image (cover). The degree of deterioration depends on the amount of external data insertion as well as step size used for DM. If this insertion process is reverted, better quality of images can be accessed. To achieve that goal, watermark bits are detected using minimum distance decoder and the remaining self-noise due to information embedding is suppressed to provide better quality of image. The simulation results have shown the validity of this claim.

关键词： Quality control

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Integrated Detect-Track Framework for Multi-view Face Detection in Video

Integrated Detect-Track Framework for Multi-view Face Detect...

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

作者： Anoop, K. R. Anandathirtha, Paresh Ramakrishnan, K. R. Kankanhalli, Mohan S. Indian Inst Sci Dept Elect Engn Bangalore 560012 Karnataka India Natl Univ Singapore Sch Comp Singapore Singapore

ISBN: (纸本)9781424442195

An Experiential sampling and Meanshift tracker based Multi-view face detection in video is proposed in this paper In this framework, instead of performing face detection at every position in a frame, we determine certain key positions to run the multiview face detectors. These key positions are statistical samples drawn from a density function that is estimated based on color cues, past detection results, Meanshift tracker results and a temporal continuity model. These samples are then propogated using a Particle filter framework. We use a Meanshift tracker to track faces that are missed by the multiview face detectors. Our framework results in a significant reduction in computation time and accounts for the detection of complete 180 degree pose of the face. We also come up with a novel likelihood measure for track termination, which becomes important when used for detection purposes.

关键词： Face recognition

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VidSeg-GAN: Generative Adversarial Network for Video Object Segmentation Tasks 11

VidSeg-GAN: Generative Adversarial Network for Video Object ...

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11th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Adak, Saptakatha Das, Sukhendu Indian Inst Technol Madras Chennai Tamil Nadu India

ISBN: (纸本)9781450366151

Video object segmentation aims to segment objects in a video sequence, given some user annotation which indicates the object of interest. Although Convolutional Neural Networks (CNNs) have been used in the recent past for the purpose of foreground segmentation in videos, adversarial training methods have not been used effectively to solve this problem, in spite of its extensive use for solving many other problems in computer vision. Earlier, flow features and motion trajectories have been extensively used to capture the temporal consistency between subsequent frames to segment moving objects in videos. However, we show that our proposed framework of processing the video frames independently using a deep generative adversarial network (GAN), is able to maintain the temporal coherency across frames without the use of any explicit trajectory based information, to provide superior results. Our main contribution lies in introducing a GAN based framework along with the incorporation of an Intersection-over-Union score based novel cost function for training the model, to solve the problem of foreground object segmentation in videos. The proposed method, when evaluated on popular real-world video segmentation datasets viz. DAVIS, SegTrack-v2 and YouTube-Objects, exhibits substantial performance gain over the recent state-of-the-art methods.

关键词： Generative adversarial networks

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Event Recognition in Broadcast Soccer Videos 16

Event Recognition in Broadcast Soccer Videos

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

作者： Saraogi, Himangi Sharma, Rahul Anand Kumar, Vijay IIIT Hyderabad Ctr Visual Informat Technol Hyderabad Telangana India

ISBN: (纸本)9781450347532

Automatic recognition of important events in soccer broadcast videos plays a vital role in many applications including video summarization, indexing, content-based search, and in performance analysis of players and teams. This paper proposes an approach for soccer event recognition using deep convolutional features combined with domain-specific cues. For deep representation, we use the recently proposed trajectory based deep convolutional descriptor (TDD) [1] which samples and pools the discriminatively trained convolutional features around the improved trajectories. We further improve the performance by incorporating domain specific knowledge based on camera view type and its position. The camera position and view type captures the statistics of occurrence of events in different play-field regions and zoom-level respectively. We conduct extensive experiments on 6 hour long soccer matches and show the effectiveness of deep video representation for soccer and the improvements obtained using domain-specific cues.

关键词： Soccer event recognition deep convolutional features playground registeration view-shot estimation

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Don't See Me, Just Filter Me: Towards secure cloud based filtering using Shamir's secret sharing and POB number system 16

Don't See Me, Just Filter Me: Towards secure cloud based fil...

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

作者： Singh, Priyanka Agarwal, Nishant Raman, Balasubramanian Indian Inst Technol Roorkee Uttar Pradesh India Natl Inst Technol Kurukshetra Kurukshetra Haryana India

ISBN: (纸本)9781450347532

Cloud computing paradigm is attracting individuals as well as organizations all round the globe due to its multiple facilities of powerful resources, storage hubs, computational power and cost effective solutions. However, distributed cloud data centers pose the threat of security breaches to the privacy of the data and pose high risks. A secured image data sharing scheme over cloud domain based on the Shamir's secret sharing and permutation ordered binary number system has been proposed here. It distributes the image information into multiple random shares that reveal no information and thus can be stored securely over the distributed cloud data centers. Different image operations could be applied in the encrypted domain over the cloud servers itself. This approach reduces the threat to security which is a major hindrance in utilizing the facilities of the cloud based architecture. Only the authentic owner possessing the secret keys could restore back the original image information from the random shares. Comparative results for both the plain domain as well as the encrypted domain have been presented to validate the efficiency of using the various image filtering operations like motion blur, unsharp masking, weiner, gaussian etc in the encrypted domain over cloud.

关键词： Cloud Computing Shamir's Secret Sharing Permutation Ordered Binary Number System Encrypted Domain

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