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检索条件"任意字段=Proceedings of the Fourteenth Indian Conference on Computer Vision, Graphics and Image Processing"

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Weighted Fast Dynamic Time Warping based multi-view human activity recognition using a RGB-D sensor

Weighted Fast Dynamic Time Warping based multi-view human ac...

引用

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

作者： Ishan Agarwal Alok Kumar Singh Kushwaha Rajeev Srivastava Department of Computer Sc. and Engineering Jaypee Institute of Information Technology Noida UP India Indian Institute of Technology Delhi New Delhi Delhi IN Department of Computer Sc. and Engineering Indian Institute of Technology (BHU) Varanasi UP India

In this paper, a real time multi-view human activity recognition model using a RGB-D (Red Green Blue-Depth) sensor is proposed. The method receives as input RGB-D data streams in real time from a Kinect for Windows V2 sensor. Initially, a skeleton-tracking algorithm is applied which gives 3D joint information of 25 unique joints. The presented approach uses a weighted version of the Fast Dynamic Time Warping that weighs the importance of each skeleton joint towards the Dynamic Time Warping (DTW) similarity cost. To recognize multi-view human activities, the weighted Dynamic Time Warping warps a time sequence of joint positions to reference time sequences and produces a similarity value. Experimental results demonstrate that the proposed method is robust, flexible and efficient with respect to multiple views activity recognition, scale and phase variations activities at different realistic scenes.

关键词： Time series analysis Heuristic algorithms Real-time systems Cameras Robustness computers image recognition

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Cross-modal attribute based facial image retrieval

Cross-modal attribute based facial image retrieval

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

作者： Dasharath Mali Soma Biswas Department of Electrical Engineering Indian Institute of Science Bangalore India

Attribute-based facial image retrieval has wide range of applications, such as in law enforcement, online social networks, etc. The problem becomes more challenging if the images are from different modalities. For example, the input is a sketch or a composite image, and the task is to retrieve photo images which have the same facial attributes as the input data. In this work, we propose a learning-based approach, in which two transformations are learnt to transform the training images from the two modalities with associated attribute annotations such that images which have similar attributes move closer to each other, and images with very different attributes move farther from each other in the transformed space. Given a query image, it is first transformed to the learnt space in which the images with similar attributes are retrieved. The same framework works seamlessly if the images to be retrieved are of same or different modality as compared to the query data. The attributes of the query image are also automatically obtained as a byproduct of the algorithm. Extensive experimental evaluation on three datasets shows the effectiveness of the proposed approach.

关键词： image retrieval Training Face Mouth Testing Law enforcement

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A new Motion Estimation Technique for video compression

A new Motion Estimation Technique for video compression

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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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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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Binary image Classification Using Machine Learning and Deep Quantum Neural Networks 14

Binary Image Classification Using Machine Learning and Deep ...

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14th International conference on Cloud Computing, Data Science and Engineering, Confluence 2024

作者： Mehta, Vaishali Kumar, Avinash Nahar, Kanchan Poonam Sharma, Dolly Tiwari, Rohak MMDU Mullana Cse Dept. Haryana Ambala India DCRUST Murthal Cse Dept. Haryana Sonepat India Geeta University Cse Dept. Haryana Panipat India Lntce Cse Dept. Haryana Panipat India Amity University Cse Dept. Greater Noida India DPS Rkpuram Greater Noida India

ISBN: (纸本)9798350344837

This paper helps to explore the intricate task of natural and precise image grouping for effective organization and retrieval. High precision in image classification is challenging due to the complexity of images and the vast array of defining features. Deep learning-based artificial intelligence, a rapidly progressing field, plays a crucial role in various industries such as image classification, computer vision, text mining, voice recognition, and medical scan analysis. Deep convolutional neural networks (CNNs) excel in advanced image categorization and processing, particularly for high-resolution images. This study introduces a deep quantum neural network (QNN) technique for binary image categorization, delving into the latest research on image classification using cross-entropy functions, deep learning, and convolutional neural networks. © 2024 IEEE.

关键词： Deep neural networks

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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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High performance VLSI implementation of Context-based Adaptive Variable Length Coding (CAVLC) for H.264 encoder

High performance VLSI implementation of Context-based Adapti...

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

作者： R. Mukherjee V. Mahajan I. Chakrabarti S. Sengupta Department of Electronics & Electrical Communication Engineering Indian Institute of Technology Kharagpur India

The video coding standard H.264 uses Context-based Adaptive Variable Length Coding (CAVLC) as one of its entropy encoding techniques. This paper proposes VLSI architecture for CAVLC algorithm. The designed hardware meets the required speed of H.264 without compromising the hardware cost. The CAVLC encoder works at a maximum clock frequency of 126 MHz when implemented in Xilinx 10.1i, Virtex-5 technology. The speed is quite appreciable when compared to other existing works. The implemented architecture meets the required rate for processing of HD-1080 format video sequence.

关键词： Table lookup Encoding Standards Video coding Hardware Read only memory Field programmable gate arrays

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Tri-modal biometric fusion for human authentication by tracking Differential Code Pattern

Tri-modal biometric fusion for human authentication by track...

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

作者： Aditya Nigam Phalguni Gupta School of Computing and Electrical Engineering Indian Institute of Technology Mandi India CSE Department NITTTR Kolkata Salt Lake India

Human authentication can now be seen as a crucial social problem. In this paper a multimodal authentication system is presented which is highly reliable and fuses iris, finger-knuckle-print and palmprint image matching scores. Segmented ROI are preprocessed using DCP (Differential Code Pattern) to obtain robust corner features. Later they are matched using the GOF (Global Optical Flow) based dissimilarity measure. The proposed system has been tested on Casia Interval and Lamp iris, PolyU finger-knuckle-print and PolyU and Casia palmprint, public databases. The proposed system has shown good performance over all unimodal databases while over multimodal (fusion of all three) databases it has shown perfect performance (i.e. CRR = 100% with EER = 0%).

关键词： Databases Iris recognition Optical imaging Iris Feature extraction Biomedical optical imaging

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Robust control of applications by hand-gestures

Robust control of applications by hand-gestures

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

作者： Aakash Anuj Tanwi Mallick Partha Pratim Das Arun Kumar Majumdar Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India

We use the RGB-D technology of Kinect to control an application with hand-gestures. We use PowerPoint for test. The system can start/end PPT, navigate between slides, capture or release the control of the cursor, and control it through natural gestures. Such a system is useful and hygienic in the kitchen, lavatories, hospital ICUs for touch-less surgery, and the like. The challenge is to extract meaningful gestures from continuous hand motions. We propose a system that recognizes isolated gestures from continuous hand motions for multiple gestures in real-time. Experimental results show that the system has 96.48% precision (at 96.00% recall) and performs better than the Microsoft Gesture Recognition library for swipe gestures.

关键词： Hidden Markov models Trajectory Hip Gesture recognition Tracking Navigation Training

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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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