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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 ...

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

作者： Manu Tom R. Venkatesh Babu Video Analytics Laboratory SERC Indian Institute of Science Bangalore India

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 (4×4) 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： Streaming media Motion segmentation conferences Video surveillance Quantization (signal) image coding

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A new Motion Estimation Technique for video compression

A new Motion Estimation Technique for video compression

引用

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

作者： K. V. Arya Purnima Prasad ABV-Indian Institute of Information Technology & Management Gwalior India

The popular techniques to eliminate temporal redundancy in video sequences are Motion Estimation and Motion Compensation. These techniques have also been used in popular H.264, MPEG-2 and MPEG-4 video coding standards. Conventional fast Block Matching Algorithms (BMA) perform exhaustive search between the current and the reference frame. Although BMA technique gives the exact result but it is computationally very expensive. Another drawback of this method is that it easily gets trapped into the local minima which eventually lead to degradation of the video quality. The proposed Motion Estimation Technique exploits the fact that the human eyes are incapable of detecting different frames when they are run at particular frame rate. The experimental results on various video sequences demonstrate that the proposed technique has outperformed all the existing conventional motion estimation techniques.

关键词： Motion estimation PSNR Vectors Sun Video sequences Databases Signal processing algorithms

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Script independent detection of bold words in multi font-size documents

Script independent detection of bold words in multi font-siz...

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

作者： Pedamalli Saikrishna A.G. Ramakrishnan Dept. of Electrical Engg Indian Institute of Science Bangalore India

A script independent, font-size independent scheme is proposed for detecting bold words in printed pages. In OCR applications such as minor modifications of an existing printed form, it is desirable to reproduce the font size and characteristics such as bold, and italics in the OCR recognized document. In this morphological opening based detection of bold (MOBDoB) method, the binarized image is segmented into sub-images with uniform font sizes, using the word height information. Rough estimation of the stroke widths of characters in each sub-image is obtained from the density. Each sub-image is then opened with a square structuring element of size determined by the respective stroke width. The union of all the opened sub-images is used to determine the locations of the bold words. Extracting all such words from the binarized image gives the final image. A minimum of 98 % of bold words were detected from a total of 65 Tamil, Kannada and English pages and the false alarm rate is less than 0.4 %.

关键词： Optical character recognition software image segmentation Electronic mail Text recognition Text analysis Character recognition

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An optimized derivative projection warping approach for moving platform video stabilization

An optimized derivative projection warping approach for movi...

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

作者： Deepika Shukla Rajib Kumar Jha Electronics and Communication Engineering Indian Institute of Information Technology Jabalpur India Department of Electrical Engineering Indian Institute of Technology Patna Patna India

This paper presents an optimized and efficient video stabilization technique based on projection curve warping. In most of the recorded videos, the relative displacement between two consecutive frames goes from 3-4 pixel for hand-held and 25-30 for moving platform applications. Based on this experimental data, the use of Sakoe-Chiba band with fixed window size has been proposed for constraining distance matrix estimation, in the dynamic time warping algorithm. In the existing projection based stabilization techniques, intensity values are matched for motion estimation. Any change in the local intensity values either induced due to intensity variation, moving objects or scene variation, causes error in the estimated motion. To overcome this problem, a higher level feature i.e. shape of the projection curve has been incorporated by matching the local derivative of curve instead of the intensity values itself. Robustness and time efficiency of the proposed technique is measured in terms of interframe transformation fidelity and processing time respectively.

关键词： Shape Motion estimation Dynamics Robustness Vectors Feature extraction Coplanar waveguides

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STAR: A Content Based Video Retrieval system for moving camera video shots

STAR: A Content Based Video Retrieval system for moving came...

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

作者： Chiranjoy Chattopadhyay Sukhendu Das Department of Computer Science and Engineering Indian Institute of Technology Madras India

This paper presents the design of STAR (Spatio-Temporal Analysis and Retrieval), an unsupervised Content Based Video Retrieval (CBVR) System. STAR's key insight and primary contribution is that it models video content using a joint spatio-temporal feature representation and retrieves videos from the database which have similar moving object and trajectories of motion. Foreground moving blobs from a moving camera video shot are extracted, along with a trajectory for camera motion compensation, to form the space-time volume (STV). The STV is processed to obtain the EMST-CSS representation, which can discriminate across different categories of videos. Performance of STAR has been evaluated qualitatively and quantitatively using precision-recall metric on benchmark video datasets having unconstrained video shots, to exhibit efficiency of STAR.

关键词： Cameras Feature extraction Trajectory Surface treatment Shape Benchmark testing Vectors

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indian Movie Face Database: A benchmark for face recognition under wide variations

Indian Movie Face Database: A benchmark for face recognition...

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

作者： Shankar Setty Moula Husain Parisa Beham Jyothi Gudavalli Menaka Kandasamy Radhesyam Vaddi Vidyagouri Hemadri J C Karure Raja Raju B Rajan Vijay Kumar C V Jawahar BVBCET Hubli Vickramce TCE SDM Dharwad PSYEC

Recognizing human faces in the wild is emerging as a critically important, and technically challenging computer vision problem. With a few notable exceptions, most previous works in the last several decades have focused on recognizing faces captured in a laboratory setting. However, with the introduction of databases such as LFW and Pubfigs, face recognition community is gradually shifting its focus on much more challenging unconstrained settings. Since its introduction, LFW verification benchmark is getting a lot of attention with various researchers contributing towards state-of-the-results. To further boost the unconstrained face recognition research, we introduce a more challenging indian Movie Face Database (IMFDB) that has much more variability compared to LFW and Pubfigs. The database consists of 34512 faces of 100 known actors collected from approximately 103 indian movies. Unlike LFW and Pubfigs which used face detectors to automatically detect the faces from the web collection, faces in IMFDB are detected manually from all the movies. Manual selection of faces from movies resulted in high degree of variability (in scale, pose, expression, illumination, age, occlusion, makeup) which one could ever see in natural world. IMFDB is the first face database that provides a detailed annotation in terms of age, pose, gender, expression, amount of occlusion, for each face which may help other face related applications.

关键词： Face Databases Motion pictures Face recognition Lighting Manuals image resolution

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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

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

作者： Sanjoy Pratihar Partha Bhowmick Shamik Sural Jayanta Mukhopadhyay Department of Computer Science & Engineering Indian Institute of Technology Kharaunur India School of Information Technology Indian Institute of Technology Kharagpur India

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 hand-drawn 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 curved-as 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： Morphological operations image edge detection

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Word recognition in natural scene and video images using Hidden Markov Model

Word recognition in natural scene and video images using Hid...

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

作者： Sangheeta Roy Partha Pratim Roy Palaiahnakote Shivakumara Umapada Pal Tata Consultancy Services Kolkata India CVPR Unit Indian Statistical Institute Kolkata India University of Malaya Kuala Lumpur Malaysia

Text recognition from a natural scene and video is challenging compared to that in scanned document images. This is due to the problems of text on different sources of various styles, font variation, font size variations, background variations, etc. There are approaches for word segmentation from video and scene images to feed the word image into OCRs. Nevertheless, such methods often fail to yield satisfactory results in recognition. Therefore, in this paper, we propose to combine Hidden Markov Model (HMM) and Convolutional Neural Network (CNN) to achieve good recognition rate. Sequential gradient features with HMM help to find character alignment of a word. Later the character alignments are verified by Convolutional Neural network (CNN). The approach is tested on both video and scene data to show the effectiveness of the proposed approach. The results are found encouraging.

关键词： Hidden Markov models Text recognition Character recognition image recognition Feature extraction image segmentation Neural networks

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Multiscale noise-adaptive homomorphic filtering based speckle denoising in laser speckle imaging

Multiscale noise-adaptive homomorphic filtering based speckl...

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

作者： Kausik Basak Manjunatha Mahadevappa Pranab Kumar Dutta Indian Institute of Technology Kharagpur Kharagpur West Bengal IN

Speckle pattern forms as a result of constructive and destructive interference due to the phase difference involved in multiple backscattered photons. In coherent optical probing, speckle has a dual role as an insidious form of noise as well as a source of information for sample microstructure. This paper focuses on designing of a multiscale noise adaptive homomorphic filter (MNAHF) for speckle noise reduction (keeping the signal-carrying speckle) in laser speckle imaging (LSI). The operation has been performed based on the calculation of local statistics within a sliding window region over a successive number of time frames. It has been shown that MNAHF outperforms other speckle denoising filters from the point of image quality assessment and better visualization. It exhibits lower mean square error and Minkowski metric values with better image quality, intact structural similarity and superior signal to noise ratio relative to others. Therefore, over a wider spectrum, this work brings out the scope of speckle noise reduction prior to further large scale processing for automated segmentation, texture analysis and image based classification techniques in clinical study of laser speckle images.

关键词： Speckle Noise Large scale integration Noise reduction Optical filters image quality Filtering

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

作者： Sudeshna Roy Sukhendu Das Department of Computer Science and Engineering Indian Institute of Technology Madras India

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 *** 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 out-performs many existing state-of-the-art methods.

关键词： image color analysis image segmentation Visualization Feature extraction Brain modeling Computational modeling Object detection

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