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检索条件"任意字段=6th Indian Conference on Computer Vision, Graphics and Image Processing"

共 2018 条记录，以下是1411-1420 订阅

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Mean Shift Clustering based Outlier Removal for Global Motion Estimation

Mean Shift Clustering based Outlier Removal for Global Motio...

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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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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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Duplicate open page removal from video stream of book flipping

Duplicate open page removal from video stream of book flippi...

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

作者： Chakraborty, Dibyayan Roy, Partha Pratim Alvarez, Jose M. Pal, Umapada Ramakrishna Mission Vivekananda Univ Dept Comp Sci Howrah India Indian Stat Inst Comp Vis & Pattern Recognit Unit Kolkata 108 India NICTA Sydney NSW Australia

ISBN: (纸本)9781479915880

Book flipping scanning refers to the process of recording a book while the user performs the flipping action of its pages. In recent years it has gained much attention as it reduces the workload of book digitization significantly. It is a challenging task because flipping at random speed and direction causes difficulties to identify distinct open page images (OPI) which represent each page of the book. In this paper, we propose a fast technique for removing duplicate open pages introduced in the video stream due to erroneous flipping. We present an algorithm that exploits cues from edge information of flipping pages. the nature of the cues extracted from the region of interest (ROI) of the frame, determines the flipping or an open state of a page whereas temporal position a flipping page determines the direction of the flipping. Combining these information we decide whether an open page image is a duplicate or not. Experiments are performed on video documents recorded using a standard resolution camera to validate the duplicate open page removal algorithm and we have obtained 95% accuracy.

关键词： Book flipping scanning Video document image OPI

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MRF and DP Based Specular Surface Reconstruction

MRF and DP Based Specular Surface Reconstruction

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

作者： Redddy, Ravindra K. Namboodiri, Anoop Int Inst Informat Technol Ctr Visual Informat Technol Hyderabad 500032 Andhra Pradesh India

ISBN: (纸本)9781479915880

this paper addresses the problem of reconstruction of specular surfaces using a combination of Dynamic Programming and Markov Random Fields formulation. Unlike traditional methods that require the exact position of environment points to be known, our method requires only the relative position of the environment points to be known for computing approximate normals and infer shape from them. We present an approach which estimates the depth from dynamic programming routine and MRF stereo matching and use MRF optimization to fuse the results to get the robust estimate of shape. We used smooth color gradient image as our environment texture so that shape can be recovered using just a single shot. We evaluate our method using synthetic experiments on 3D models like Stanford bunny and show the real experiment results on golden statue and silver coated statue.

关键词： specular surface data processing dynamic programming MYRF gene Environments statues single-shot Surface reconstruction Reconstructive Surgical Procedures color gradients Reconstructions

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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...

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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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Classification of Hardwood Species using ANN Classifier

Classification of Hardwood Species using ANN Classifier

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

作者： Yadav, Arvind R. Dewal, M. L. Anand, R. S. Gupta, Sangeeta Indian Inst Technol Dept Elect Engn Roorkee Uttar Pradesh India Forest Res Inst Bot Div Dehra Dun India

ISBN: (纸本)9781479915880

In this paper, an approach for the classification of different hardwood species of open access database, using texture feature extraction and supervised machine learning technique has been implemented. Edges of complex cellular structure of microscopic images of hardwood are enhanced with the application of Gabor filter, and Gray Level Co-occurrence Matrix (GLCM) as an effective texture feature extraction technique is being revalidated. About, 44 features have been extracted from GLCM;these features have been further normalized in the range [0.1, 1]. Multilayer Perceptron Backpropagation Artificial Neural Network have been used for classification. Experiments conducted on 25 wood species have resulted in recognition accuracy of about 88.60% and 92.60% using Levenberg-Marquardt backpropagation training function with two different datasets for training, validation and testing ratio (70%, 15%, 15% and 80%, 10%, 10%) respectively. Proposed methodology can be extended with optimized machine learning techniques for online identification of wood.

关键词： Microscopic image GLCM Gabor Filter Multilayer Perceptron Backpropagation Artificial Neural Network Reciever Operating Characteristics

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Spatio-Temporal feature based VLAD for efficient Video retrieval

Spatio-Temporal feature based VLAD for efficient Video retri...

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

作者： Reddy, Mopuri K. Arora, Sahil Babu, R. Venkatesh Indian Inst Sci Video Analyt Lab SERC Bengaluru Karnataka India Indian Inst Technol Kharagpur Dept Comp Sci & Engn Kharagpur W Bengal India

ISBN: (纸本)9781479915880

Compact representation of visual content has emerged as an important topic in the context of large scale image/video retrieval. the recently proposed Vector of Locally Aggregated Descriptors (VLAD) has shown to outperform other existing techniques for retrieval. In this paper, we propose two spatio-temporal features for constructing VLAD vectors for videos in the context of large scale video retrieval. Given a particular query video, our aim is to retrieve similar videos from the database. Experiments are conducted on UCF50 and HMDB51 datasets, which pose challenges in the form of camera motion, view-point variation, large intra-class variation, etc. the paper proposes the following two spatio-temporal features for constructing VLADs i) Local Histogram of Oriented Optical Flow (LHOOF), and ii) Space-Time Invariant Points (STIP). the performance of these proposed features are compared with SIFT based spatial feature. the mean average precision (MAP) indicates the better retrieval performance of the proposed spatio-temporal feature over spatial feature.

关键词： Vector of Locally Aggregated Descriptors (VLAD) Video Retrieval STIP HOOF SIFT Spatio-temporal features

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Removal of Hand-drawn Annotation Lines from Document images by Digital-geometric Analysis and Inpainting

Removal of Hand-drawn Annotation Lines from Document Images ...

引用

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

作者： Pratihar, Sanjoy Bhowmick, Partha Sural, Shamik Mukhopadhyay, Jayanta Indian Inst Technol Dept Comp Sci & Engn Kharagpur 721302 W Bengal India Indian Inst Technol Sch Informat Technol Kharagpur 721302 W Bengal India

ISBN: (纸本)9781479915880

Performance of an OCR system is badly affected due to presence of hand-drawn annotation lines in various forms, such as underlines, circular lines, and other text-surrounding curves. Such annotation lines are drawn by a reader usually in free hand in order to summarize some text or to mark the keywords within a document page. In this paper, we propose a generalized scheme for detection and removal of these handdrawn annotations from a scanned document page. An underline drawn by hand is roughly horizontal or has a tolerable undulation, whereas for a hand-drawn curved line, the slope usually changes at a gradual pace. Based on this observation, we detect the cover of an annotation object-be it straight or curvedas a sequence of straight edge segments. the novelty of the proposed method lies in its ability to compute the exact cover of the annotation object, even when it touches or passes through any text character. After getting the annotation cover, an effective method of inpainting is used to quantify the regions where text reconstruction is needed. We have done our experimentation with various documents written in English, and some results are presented here to show the efficiency and robustness of the proposed method.

关键词： ANNOTATIONS hand-drawn inpaint STRAIGHT-EDGE document image lines lines texts

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ISIgraphy: a Tool for Online Handwriting Sample Database Generation

<i>ISIgraphy</i>: a Tool for Online Handwriting Sample Datab...

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

作者： Das, Arindam Bhattacharya, Ujjwal Narula Inst Technol Dept Comp Sci & Engn Kolkata India Indian Stat Inst Comp Vis & Pattern Recognit Unit Kolkata India

ISBN: (纸本)9781479915880

Online handwriting recognition research has recently received significant thrust. Specifically for indian scripts, handwriting recognition has not been focused much till in the near past. However, due to generous Government funding through the group on Technology Development for indian Languages (TDIL) of the Ministry of Communication & Information Technology (MC&IT), Govt. of India, research in this area has received due attention and several groups are now engaged in research and development works for online handwriting recognition in different indian scripts. An extensive bottleneck of the desired progress in this area is the difficulty of collection of large sample databases of online handwriting in various scripts. Towards the same, recently a user-friendly tool on Android platform has been developed to collect data on handheld devices. this tool is called ISIgraphy and has been uploaded in the Google Play for free download. this application is designed well enough to store handwritten data samples in large scales in user-given file names for distinct users. Its use is script independent, meaning that it can collect and store handwriting samples written in any language, not necessarily an indian script. It has an additional module for retrieval and display of stored data. Moreover, it can directly send the collected data to others via electronic mail.

关键词： Online handwriting recognition database generation online handwriting database

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REAL TIME ANOMALY DETECTION IN H.264 COMPRESSED VIDEOS

REAL TIME ANOMALY DETECTION IN H.264 COMPRESSED VIDEOS

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

作者： Biswas, Sovan Babu, R. Venkatesh Indian Inst Sci Supercomp Educ Res Ctr Video Analyt Lab Bangalore 560012 Karnataka India

ISBN: (纸本)9781479915880

Real time anomaly detection is the need of the hour for any security applications. In this paper, we have proposed a real-time anomaly detection algorithm by utilizing cues from the motion vectors in H.264/AVC compressed domain. the discussed work is principally motivated by the observation that motion vectors (MVs) exhibit different characteristics during anomaly. We have observed that H.264 motion vector magnitude contains relevant information which can be used to model the usual behavior (UB) effectively. this is subsequently extended to detect abnormality/anomaly based on the probability of occurrence of a behavior. Additionally, we have suggested a hierarchical approach through Motion Pyramid for High Resolution videos to further increase the detection rate. the proposed algorithm has performed extremely well on UMN and Peds Anomaly Detection Video datasets, with a detection speed of > 150 and 65 - 75 frames per sec in respective datasets resulting in more than 200x speedup along with comparable accuracy to pixel domain state-of-the-art algorithms.

关键词： Anomaly Detection H.264/AVC Compressed Domain Real Time Detection Video Surveillance

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