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检索条件"任意字段=15th Indian Conference on Computer Vision Graphics and Image Processing"

共 1004 条记录，以下是121-130 订阅

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Robust Video Watermarking Resilient to Temporal Scalability 5

Robust Video Watermarking Resilient to Temporal Scalability

引用

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

作者： Sahu, Nilkanta Tiwari, Vivek Sur, Arijit IIT Guwahati Dept CSE Gauhati 781039 India

ISBN: (纸本)9781467385640

In this paper, an uncompressed domain video watermarking scheme resilient to temporal adaptation is proposed for scalable video coding. In the proposed scheme, each temporal layer has been separately embedded with a different watermark which is generated by DCT domain decomposition of a single watermark image. A zigzag sequence of block wise DCT coefficients of the watermark image is partitioned into non-overlapping sets and each set is embedded separately into different temporal layers. the base layer is embedded with the first set of DCT coefficient (which includes DC coefficient of each block) and successive layers are embedded with successive nonoverlapping coefficient sets. the coefficients of each set is chosen in such a fashion that uniform energy distribution across all temporal layers can be maintained. Experimental results show that the proposed scheme is robust against temporal scalability and robustness of the watermark increases with the addition of successive enhancement layers.

关键词： Scalability

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Single Shot High Dynamic Range Imaging using Histogram Separation and Exposure Fusion 5

Single Shot High Dynamic Range Imaging using Histogram Separ...

引用

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

作者： Johnson, Anoop K. Jiji, C. V. Mar Baselios Coll Engn & Technol Dept Elect & Commun Engn Trivandrum Kerala India Coll Engn Dept Elect & Commun Engn Trivandrum Kerala India

ISBN: (纸本)9781467385640

Conventionally, High Dynamic Range (HDR) images are generated by fusing multiple exposure Low Dynamic Range (LDR) images, where the HDR output often suffers from artifacts due to misalignment of camera and presence of dynamic objects in the scene. An efficient approach to overcome these issues is to use single shot HDR imaging. In this paper, we propose a method for generating an HDR image from a single LDR image. We first generate multiple exposures of the given scene using histogram separation by adopting varying bin sizes. the resulting LDR images are fused making use of the quality measures such as contrast, saturation and well - exposedness. the results show the effectiveness of the proposed approach which is verified qualitatively and in terms of various quantitative measures.

关键词： Graphic methods

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High Quality Depth Map Estimation by Kinect Upsampling and Hole Filling using RGB Features and Mutual Information

High Quality Depth Map Estimation by Kinect Upsampling and H...

引用

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

作者： Chahal, Nidhi Chaudhury, Santanu Indian Inst Technol Dept Elect Engn Delhi India

ISBN: (纸本)9781479915880

High quality depth map estimation is required for better visualization of 3D views as there is great impact of depth map quality on overall 3D image quality. If the depth is estimated from conventional ways using two or more images, some defects come into picture, mostly in regions without texture. We utilised Microsoft Kinect RGBD dataset to obtain input color images and depth maps which also includes some noise factors. We proposed a method to remove this noise and get quality depth images. First the color and depth images are aligned to each other using intensity based image registration. this method of image alignment is mostly used in medical field, but we applied this technique to correct kinect depth maps by which one can avoid cumbersome task of feature based point correspondence between images. there is no requirement of preprocessing or segmentation steps if we use intensity based image alignment method. Second, we proposed an algorithm to fill the unwanted gaps in kinect depth maps and upsampled it using corresponding high resolution color image. Finally we applied 9x9 median filtering on implementation results and get high quality and improved depth maps.

关键词： image registration mutual information geometric transformations

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Fast Moving- Object Detection in H.264/AVC Compressed Domain for Video Surveillance

Fast Moving- Object Detection in H.264/AVC Compressed Domain...

引用

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

作者： Tom, Manu Babu, R. Venkatesh Indian Inst Sci SERC Video Analyt Lab Bangalore 560012 Karnataka India

ISBN: (纸本)9781479915880

this paper discusses a novel fast approach for moving object detection in H.264/AVC compressed domain for video surveillance applications. the proposed algorithm initially segments out edges from regions with motion at macroblock level by utilizing the gradient of quantization parameter over 2D-image space. A spatial median filtering of the segmented edges followed by weighted temporal accumulation accounts for whole object segmentation. To attain sub-macroblock (4 x 4) level precision, the size of macroblocks (in bits) is interpolated using a two tap filter. Partial decoding rules out the complexity involved in full decoding and gives fast foreground segmentation results. Compared to other compressed domain techniques, the proposed approach allows the video streams to be encoded with different quantization parameters across macroblocks thereby increasing flexibility in bit rate adjustment.

关键词： Motion Segmentation Compressed Domain H.264/AVC Video Surveillance QP-delta

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Smart city solutions for location tracking 15

Smart city solutions for location tracking

引用

International conference on computer graphics, Visualization, computer vision and image processing 2021, CGVCVIP 2021, Connected Smart Cities 2021, CSC 2021 and Big Data Analytics, Data Mining and Computational Intelligence 2021, BIGDACI 2021 - Held at the 15th Multi-conference on computer Science and Information Systems, MCCSIS 2021

作者： Bhati, Neetesh Shetty, Sujala D. Raj, Aparna Department of Computer Science Birla Institute of Technology and Science Pilani India

ISBN: (纸本)9789898704320

With the advancement in technology cities are getting smarter and becoming more livable and responsive. In the next few years, we expect a significant rise in the use of data and technology to make better decisions and improve the quality of life. Outdoor navigation using GPS is relatively easy but finding way indoors is still considered as a frenetic task. We aim to use data from multiple sources to create a detailed profile of the geographic information for every individual which can be easily used and securely accessed whenever needed. In this paper, we propose a method for indoor navigation which guides the user to a specific spot using smart phones. Here A* algorithm is used to find the shortest path between two points on the map and ArcGIS software for creating the map data. the generated map along with the required services are hosted on Osiris, an open-source indoor map rest API server. the sever is connected to a front end using an Android application developed with Android Studio. this can be applied across large companies which are situated in sprawling campuses. © 2021 International conference on computer graphics, Visualization, computer vision and image processing 2021, CGVCVIP 2021, Connected Smart Cities 2021, CSC 2021 and Big Data Analytics, Data Mining and Computational Intelligence 2021, BIGDACI 2021 - Held at the 15th Multi-conference on computer Science and Information Systems, MCCSIS 2021. All rights reserved.

关键词： Geographic information systems

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An Enhanced Decision Based Unsymmetric Trimmed Median Filter For Removal of High Density Salt and Papper Noise 5

An Enhanced Decision Based Unsymmetric Trimmed Median Filter...

引用

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

作者： Singh, Shruti Tiwari, Anil Kumar LNM Inst Informat Technol Jaipur Rajasthan India Indian Inst Technol Jodhpur Jodhpur Rajasthan India

ISBN: (纸本)9781467385640

this paper proposes a new algorithm for restoration of gray scale images corrupted by salt and pepper noise(SPN). the proposed algoritm identifies a pixel as noisy if its intensity value is 0 or 255 and processes it using pixels in a 3 x 3 window. If the window consists of noisy and non-noisy pixels, then the pixel to be processed is replaced with the trimmed median value of the non-noisy pixels. However, if only noisy pixels are there in the window then their mean value is used to process the pixel. the proposed method uses processed (i.e. the de-noised) pixels in the window while processing the noisy pixels and shows significantly better performance, particularly at high noise density, as compared to various methods reported in literature. Experimental results show improvements both visually and quantitatively compared to other reported methods.

关键词： Impulse noise salt and pepper noise image de-noising Median filter asymmetric trimmed median filter Decision based filter

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A Novel Stereo Matching Approach for Pedestrian Re-identification 5

A Novel Stereo Matching Approach for Pedestrian Re-identific...

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

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

ISBN: (纸本)9781467385640

Automatic and reliable identification of pedestrians from multiple camera views is very important for video surveillance and can save a lot of manual effort. the significant variations in viewpoints, poses, illumination and occlusions makes this problem very challenging. Most of the existing approaches addressing this problem handle drastic viewpoint change in a supervised way and thus require labelling new training data for a different pair of camera views. In this paper, we present a novel approach for pedestrian re-identification using stereo matching, which does not require any kind of training. the cost of the stereo matching of two images is used for evaluating the similarity of the images, without performing 3-D reconstruction. We show that this cost is robust to the large pose variations observed in the images captured from multiple cameras. the proposed pedestrian re-identification algorithm is built on top of a dynamic programming stereo matching algorithm. Experimental evaluation on the challenging VIPeR dataset shows the effectiveness of the proposed approach.

关键词： Dynamic programming

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Analysis of capsule networks for image classification 15

Analysis of capsule networks for image classification

引用

作者： Goceri, Evgin Biomedical Engineering Department Engineering Faculty Akdeniz University Dumlupinar Boulevard Antalya07058 Turkey

ISBN: (纸本)9789898704320

Recently, the interest in convolutional neural networks have grown exponentially for image classification. their success is based on the ability to learn hierarchical and meaningful image representation that results in a feature extraction technique which is general, flexible and can encode complex patterns. However, these networks have some drawbacks. For example, they need a large number of labeled data, lose valuable information (about the internal properties, such as shape, location, pose and orientation in an image and their relationships) in the pooling and are not able to encode deformation information. therefore, capsule based networks have been introduced as an alternative to convolutional neural networks. Capsules are a group of neurons (logistic units) representing the presence of an entity and the vector indicating the relationship between features by encoding instantiation parameters. Unlike convolutional neural networks, maximum pooling layers are not employed in a capsule network, but a dynamic routing mechanism is applied iteratively in order to decide the coupling of capsules between successive layers. In other words, training between capsule layers is provided with a routing-by-agreement method. However, capsule networks and their properties to provide high accuracy for image classification have not been sufficiently investigated. therefore, this paper aims (i) to point out drawbacks of convolutional networks, (ii) to examine capsule networks, (iii) to present advantages, weaknesses and strengths of capsule networks proposed for image classification. © 2021 International conference on computer graphics, Visualization, computer vision and image processing 2021, CGVCVIP 2021, Connected Smart Cities 2021, CSC 2021 and Big Data Analytics, Data Mining and Computational Intelligence 2021, BIGDACI 2021 - Held at the 15th Multi-conference on computer Science and Information Systems, MCCSIS 2021. All rights reserved.

关键词： Convolution

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Learning Metrics for Diversity in Instance Retrieval 5

Learning Metrics for Diversity in Instance Retrieval

引用

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

作者： Rao, Vidyadhar Gupta, Ajitesh Chari, Visesh Jawahar, C. V. IIIT Hyderabad Ctr Visual Informat Technol Hyderabad Andhra Pradesh India

ISBN: (纸本)9781467385640

Instance retrieval (IR) is the problem of retrieving specific instances of a particular object, like a monument, from a collection of images. Currently, the most popular methods for IR use Bag of words (BoW) features for retrieval. However, a prominent problem for IR remains the tendency of BoW based methods to retrieve near-identical images as most relevant results. In this paper, we define diversity in IR as variation of physical properties among most relevant retrieved results for a query image. To achieve this, we propose both an ITML algorithm that re-fashions the BoW feature space into one that appreciates diversity better, and a measure to evaluate diversity in retrieval results for IR applications. Additionally, we also generate 200 hand-labeled images from the Paris dataset, for use in further research in this area. Experiments on the popular Paris dataset show that our method outperforms the standard BoW model in many cases.

关键词： computer vision

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Report on estimating rice field quality using artificial intelligence 15

Report on estimating rice field quality using artificial int...

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作者： Khatraty, Yahjeb Bouha Nauwynck, Nedra Mellouli Diallo, Mamadou Tourad Nanne, Mohamedade Farouk University of Paris 8 - Vincennes - Saint-Denis Doctoral School Cognition Language Interaction Paris France University of Nouakchott Al-Aasriya Faculty of Science and Technology Doctoral School of Computer Science Nouakchott Mauritania

ISBN: (纸本)9789898704320

the use of artificial intelligence has made life easier for farmers, as analysis of agricultural data allows farmers to make informed decisions, supported by large data sets and processed by machine learning algorithms. In this paper, we present the literature on rice quality assessment according to the different criteria and factors used to predict the quality or yield of rice. thus, we provided a list of machine learning and deep learning models that had high accuracy in predicting rice yield and quality. In addition, due to the lack of literature of a real-time rice field monitoring system, we proposed a real-time rice field condition monitoring system that collects weather and soil condition data and sends them to the web server. the farmer can see the status of its remotely field and can automate certain tasks such as irrigation based on the collected data values. © 2021 International conference on computer graphics, Visualization, computer vision and image processing 2021, CGVCVIP 2021, Connected Smart Cities 2021, CSC 2021 and Big Data Analytics, Data Mining and Computational Intelligence 2021, BIGDACI 2021 - Held at the 15th Multi-conference on computer Science and Information Systems, MCCSIS 2021. All rights reserved.

关键词： Internet of things

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