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Enhancement of camera captured text images with specular reflection

Enhancement of camera captured text images with specular ref...

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

作者： Aishwarya Visvanathan T. Chattopadhyay Ujjwal Bhattacharya Innovation Lab Kolkata Tata Consultancy Services Limited CVPR Unit Indian Statistical Institute Kolkata India

Specular reflection of light degrades the quality of scene images. Whenever specular reflection affects the text portion of such an image, its readability is reduced significantly. Consequently, it becomes difficult for an OCR software to detect and recognize similar texts. In the present work, we propose a novel but simple technique to enhance the region of the image with specular reflection. The pixels with specular reflection were identified in YUV color plane. In the next step, it enhances the region by interpolating possible pixel values in YUV space. The proposed method has been compared against a few existing general purpose image enhancement techniques which include (i) histogram equalization, (ii) gamma correction and (iii) Laplacian filter based enhancement method. The proposed approach has been tested on some images from ICDAR 2003 Robust Reading Competition image database. We computed a Mean Opinion Score based measure to show that the proposed method outperforms the existing enhancement techniques for enhancement of readability of texts in images affected by specular reflection.

关键词： image color analysis Cameras Mathematical model image enhancement image databases Ash

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Real-time human action recognition from motion capture data

Real-time human action recognition from motion capture data

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

作者： Suraj Vantigodi R. Venkatesh Babu Video Analytics Lab SERC Indian Institute of Science Bangalore India

Recognition of human actions is one of the important tasks in various computer vision applications including video surveillance, human computer interaction etc. Traditionally RGB or depth cameras are utilized for this task. In this work we propose an approach that utilizes motion capture data for recognizing actions. Motion capture provides accurate motion information of joints of body in 3D space. The 3D skeleton joint co-ordinates of the user provided by motion capture system are used to analyze the dynamics of the action being performed. The temporal variance of each joint of the skeleton and its time weighted variance serve as the features for classification. The time weighted variance feature embeds temporal information in the feature and helps in discriminating confusing actions such as sit-down and stand-up. These features can be extracted rapidly and suitable for real-time recognition. We demonstrate the performance of the proposed approach using correlation based metric and support vector machines (SVM) on the Multi-modal Human Action Detection dataset. The recognition accuracy of above 95% has been achieved.

关键词： Joints Accuracy Three-dimensional displays Feature extraction Vectors Databases

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Evolutionary design of Multiquadric radial basis functions neural network for face recognition

Evolutionary design of Multiquadric radial basis functions n...

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

作者： Vandana Agarwal Surekha Bhanot Dept. of Computer Science and Information Systems Birla Institute of Technology and Science Pilani India Dept. of Electrical and Electronics Engg./Instrumentation Birla Institute of Technology and Science Pilani India

In this paper, it is proposed to use Multiquadric basis functions at hidden layer of radial basis functions neural networks (RBFNN) for face recognition. The performance of RBFNN depends on the design of the structure of RBFNN, which includes optimal center selection and spread of RBF units, number of neurons at hidden layer, weights etc. Design of hidden layer of RBFNN also includes the choice of basis functions which is proposed to be of Multiquadric basis functions. The shape of Multiquadric basis function plays an important role in the performance of RBFNN in face recognition. A novel evolutionary shape parameter optimization technique inspired by the attractiveness of the natural fireflies is proposed and is used in the design of Multiquadric basis functions for the given face database. The algorithm is tested on two benchmarked face databases ORL and indian face databases. The proposed technique significantly outperforms the performance of the Gaussian basis functions based RBFNN in terms of face recognition accuracy.

关键词： Face Face recognition Shape Databases Accuracy Radial basis function networks

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

作者： Dibyayan Chakraborty Partha Pratim Roy Jose M. Alvarez Umapada Pal Department of computer Science Ramakrishna Mission Vivekananda University Howrah India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India NICTA Australia

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： Streaming media Feature extraction Cameras Optical character recognition software image edge detection Accuracy Performance evaluation

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

作者： Sovan Biswas R Venkatesh Babu Video Analytics Lab Supercomputer Education Research Center Indian Institute of Science Bangalore India

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 200× speedup along with comparable accuracy to pixel domain state-of-the-art algorithms.

关键词： Videos computer vision Real-time systems Training conferences Accuracy Histograms

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Design of Manipuri Keywords Spotting System using HMM

Design of Manipuri Keywords Spotting System using HMM

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

作者： Laishram Rahul Salam Nandakishor L. Joyprakash Singh S. K. Dutta North-Eastern Hill University Shillong Meghalaya IN Department of ECE Speech & Image Processing Laboratory Shillong

This paper aims to discuss the implementation of phoneme based Manipuri Keyword Spotting System (MKWSS). Manipuri is a scheduled indian language of Tibeto-Burman origin. Around 5 hours of read speech are collected from 4 male and 6 female speakers for development of database of MKWSS. The symbols of International Phonetic Alphabet (IPA)(revised in 2005) are used during the transcription of the data. A five state left to right Hidden Markov Model (HMM) with 32 mixture continuous density diagonal covariance Gaussian Mixture Model (GMM) per state is used to build a model for each phonetic unit. We have used HMM tool kit (HTK), version 3.4 for modeling the system. The system can recognize 29 phonemes and a non-speech event (silence) and will detect the present keywords formed by these phonemes. Continuous Speech data have been collected from 5 males and 8 females for analysing the performance of the system. The performance of the system depends on the ability of detection of the keywords. An overall performance of 65.24% is obtained from the phoneme based MKWSS.

关键词： Hidden Markov models Speech Vectors Speech recognition Databases Acoustics Feature extraction

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Lip tracking under varying expressions utilizing domain knowledge

Lip tracking under varying expressions utilizing domain know...

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

作者： Swapna Agarwal Dipti Prasad Mukherjee Indian Statistical Institute Kolkata

In recent years the need of a robust facial component tracking especially lip tracking algorithm has increased dramatically. We implement an active contour (snake) model inspired by human perception for lip tracking. In addition to the conventional energy terms for tension, rigidity (internal energy) and gradient magnitude (external energy) we propose to include energy terms from domain knowledge for lip shape constraint and local region profile constraint. Generalized deterministic annealing (GDA) update of the energy functional helps the solution to escape suboptimal local minima in the energy space and give better tracking result. Experimental results show that the proposed method efficiently adapts to the highly deformable lip boundaries even for lips with indistinct edges and colored (adorned) lips where gradient magnitude based or local region based tracking methods respectively fail. We have done a number of experiments to evaluate the performance of our method in comparison with the existing state-of-the-art methods.

关键词： Shape Principal component analysis Vectors Lips Active contours Markov processes Annealing

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

作者： Manish Okade Prabir Kumar Biswas Department of Electronics and Communication Engineering BVB College of Engineering and Technology Hubli India Department of Electronics and Electrical Communication Engineering Indian Institute of Technology Kharagpur India

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： Vectors Motion estimation Cameras Mathematical model Estimation Kernel Robustness

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Extraction of line-word-character segments directly from run-length compressed printed text-documents

Extraction of line-word-character segments directly from run...

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

作者： Mohammed Javed P. Nagabhushan B.B. Chaudhuri Department of Studies in Computer Science University of Mysore Mysore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Segmentation of a text-document into lines, words and characters, which is considered to be the crucial preprocessing stage in Optical Character Recognition (OCR) is traditionally carried out on uncompressed documents, although most of the documents in real life are available in compressed form, for the reasons such as transmission and storage efficiency. However, this implies that the compressed image should be decompressed, which indents additional computing resources. This limitation has motivated us to take up research in document image analysis using compressed documents. In this paper, we think in a new way to carry out segmentation at line, word and character level in run-length compressed printed-text-documents. We extract the horizontal projection profile curve from the compressed file and using the local minima points perform line segmentation. However, tracing vertical information which leads to tracking words-characters in a run-length compressed file is not very straight forward. Therefore, we propose a novel technique for carrying out simultaneous word and character segmentation by popping out column runs from each row in an intelligent sequence. The proposed algorithms have been validated with 1101 text-lines, 1409 words and 7582 characters from a data-set of 35 noise and skew free compressed documents of Bengali, Kannada and English Scripts.

关键词： image coding image segmentation Optical character recognition software Text analysis image analysis Facsimile

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

作者： Nidhi Chahal Santanu Chaudhury Department of Electrical Engineering Indian Institute of Technology Delhi India

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 9×9 median filtering on implementation results and get high quality and improved depth maps.

关键词： Mutual information image color analysis Filtering Color Joints image resolution image registration

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