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

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Leveraging information from imperfect examples : Common action sequence mining from a mix of incorrect performances 11

Leveraging information from imperfect examples : Common acti...

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11th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Jain, Hiteshi Harit, Gaurav Indian Inst Technol Jodhpur Jodhpur Rajasthan India

ISBN: (纸本)9781450366151

As much as good representation and theory are needed to explain human actions, so are the action videos used for learning good segmentation techniques. To accurately model complex actions such as diving, figure skating, and yoga practices, videos depicting action by human experts are required. Lack of experts in any domain leads to reduced number of videos and hence an improper learning. In this work we attempt to utilize imperfect amateur performances to get more confident representations of human action sequences. We introduce a novel Community Detection based unsupervised framework that provides mechanisms to interpret video data and address its limitations to produce better action representation. Human actions are composed of distinguishable key poses which form dense communities in graph structures. Anomalous poses performed for a longer duration can also form such dense communities but can be identified based on their rare occurrence across action videos and be rejected. Further, we propose a technique to learn the temporal order of these key poses from these imperfect videos, where the inter community links help reduce the search space of many possible pose sequences. Our framework is seen to improve the segmentation performance of complex human actions with the help of some imperfect performances. the efficacy of our approach has been illustrated over two complex action datasets - Sun Salutation and Warm-up exercise, that have been developed using random executions from amateur performers.

关键词： Unsupervised Anomaly Detection network modeling community detection human action segmentation

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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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2013 4th National conference on computer vision, Pattern Recognition, image processing and graphics, NCVPRIPG 2013

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

ISBN: (纸本)9781479915880

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. © 2013 IEEE.

关键词： Support vector machines

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computer vision, Imaging and computer graphics theory and Applications 1

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丛书名： Communications in computer and Information Science

1000年

作者： Kadi Bouatouch A. Augusto de Sousa Manuela Chessa Alexis Paljic Andreas Kerren Christophe Hurter Giovanni Maria Farinella Petia Radeva Jose Braz

ISBN: (数字)9783030948931

ISBN: (纸本)9783030948924

this book constitutes thoroughly revised and selected papers from the 15th International Joint conference on computer vision, Imaging and computer graphics theory and Applications, VISIGRAPP 2020, held in Valletta, Malta, in February 2020.;the 25 thoroughly revised and extended papers presented in this volume were carefully reviewed and selected from 455 submissions. the papers contribute to the understanding of relevant trends of current research on computer graphics; human computer interaction; information visualization; computer vision.

关键词： image processing and computer vision Artificial Intelligence Information Systems and Communication Service computer Appl. in Social and Behavioral Sciences computers and Education

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Learning 3D Human Pose from Structure and Motion 15th

Learning 3D Human Pose from Structure and Motion

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15th European conference on computer vision (ECCV)

作者： Dabral, Rishabh Mundhada, Anurag Kusupati, Uday Afaque, Safeer Sharma, Abhishek Jain, Arjun Indian Inst Technol Mumbai Maharashtra India Gobasco AI Labs Lucknow Uttar Pradesh India

ISBN: (纸本)9783030012403;9783030012397

3D human pose estimation from a single image is a challenging problem, especially for in-the-wild settings due to the lack of 3D annotated data. We propose two anatomically inspired loss functions and use them with a weakly-supervised learning framework to jointly learn from large-scale in-the-wild 2D and indoor/synthetic 3D data. We also present a simple temporal network that exploits temporal and structural cues present in predicted pose sequences to temporally harmonize the pose estimations. We carefully analyze the proposed contributions through loss surface visualizations and sensitivity analysis to facilitate deeper understanding of their working mechanism. Jointly, the two networks capture the anatomical constraints in static and kinetic states of the human body. Our complete pipeline improves the state-of-the-art by 11.8% and 12% on Human3.6M and MPI-INF-3DHP, respectively, and runs at 30 FPS on a commodity graphics card.

关键词： Sensitivity analysis

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Digital restoration of damaged mural images 12

Digital restoration of damaged mural images

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8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Purkait, Pulak Chanda, Bhabatosh Indian Statistical Institute Kolkata India

ISBN: (纸本)9781450316606

Patch-based techniques are proven to generate promising results and outperform many of the existing state-of-art techniques for most of the applications in digital image processing. In this work we develop a patch based coherent texture synthesis technique. A patch-based anisotropic diffusion techniques combined with a novel high-frequency generating technique that can enhance line/brush strokes is also proposed. though these techniques can be applied to many different image processing applications, here we have limited ourselves in the application to interactive digital mural painting recovery/restoration. Some empirical and practical evidence for its high quality texture synthesis and restoration for mural paintings are also presented. the experimental results show the effectiveness of the proposed algorithm. © 2012 ACM.

关键词： Restoration

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DeepFly: Towards Complete Autonomous Navigation of MAVs with Monocular Camera 16

DeepFly: Towards Complete Autonomous Navigation of MAVs with...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Shah, Utsav Khawad, Rishabh Krishna, K. Madhava IIIT Hyderabad KCIS Robot Res Ctr Hyderabad Andhra Pradesh India

ISBN: (纸本)9781450347532

Recently, the interest in Micro Aerial Vehicles (MAVs) and their autonomous flights has increased tremendously and significant advances have been made. the monocular camera has turned out to be most popular sensing modality for MAVs as it is light-weight, does not consume more power, and encodes rich information about the environment around. In this paper, we present DeepFly, our framework for autonomous navigation of a quadcopter equipped with monocular camera. the navigable space detection and waypoint selection are fundamental components of autonomous navigation system. they have broader meaning than just detecting and avoiding immediate obstacles. Finding the navigable space emphasizes equally on avoiding obstacles and detecting ideal regions to move next to. the ideal region can be defined by two properties: 1) All the points in the region have approximately same high depth value and 2) the area covered by the points of the region in the disparity map is considerably large. the waypoints selected from these navigable spaces assure collision-free path which is safer than path obtained from other waypoint selection methods which do not consider neighboring information. In our approach, we obtain a dense disparity map by performing a translation maneuver. this disparity map is input to a deep neural network which predicts bounding boxes for multiple navigable regions. Our deep convolutional neural network with shortcut connections regresses variable number of outputs without any complex architectural add on. Our autonomous navigation approach has been successfully tested in both indoors and outdoors environment and in range of lighting conditions.

关键词： Micro Aerial Vehicles Autonomous Navigation Deep Learning

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Feature Extraction and Simplification from colour images based on Colour image Segmentation and Skeletonization using the Quad-Edge data structure

Feature Extraction and Simplification from colour images bas...

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15th International conference in Central Europe on computer graphics, Visualization and computer vision

作者： Sharma, Ojaswa Mioc, Darka Anton, Francois Univ New Brunswick Dept Geodesy & Geomat Engn Fredericton NB E3B 5A3 Canada

ISBN: (纸本)9788086943022

Region features in colour images are of interest in applications such as mapping, climatology, change detection, medicine, etc. this research work is an attempt to automate the process of extracting feature boundaries from colour images. this process is an attempt to eventually replace manual digitization process by computer assisted boundary detection and conversion to a vector layer in a spatial database. In colour images, various features can be distinguished based on their colour. the features thus extracted as object border can be stored as vector maps in a spatial database after labelling and editing. Here, we present a complete methodology of the boundary extraction and skeletonization process from colour imagery using a colour image segmentation algorithm, a crust extraction algorithm and our new skeleton extraction algorithm. We also present a prototype application for completely automated or semi-automated processing of (satellite) imagery and scanned maps with an application to coastline extraction. Other applications include extraction of fields, clear cuts, clouds, as well as heating or pollution monitoring and dense forest mapping among others.

关键词： colour image segmentation polygon feature extraction satellite imagery

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GPU-Accelerated Human Motion Tracking Using Particle Filter Combined with PSO

GPU-Accelerated Human Motion Tracking Using Particle Filter ...

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15th International conference on Advanced Concepts for Intelligent vision Systems (ACIVS)

作者： Rymut, Boguslaw Kwolek, Bogdan Krzeszowski, Tomasz Rzeszow Univ Technol Rzeszow Poland AGH Univ Sci & Technol PL-30059 Krakow Poland

ISBN: (纸本)9783319028958;9783319028941

this paper discusses how to combine particle filter (PF) with particle swarm optimization (PSO) to achieve better object tracking. Owing to multi-swarm based mode seeking the algorithm is capable of maintaining multimodal probability distributions and the tracking accuracy is far better than accuracy of PF or PSO. We propose parallel resampling scheme for particle filtering running on GPU. We show the efficiency of the parallel PF-PSO algorithm on 3D model based human motion tracking. the 3D model is rasterized in parallel and single thread processes one column of the image. Such level of parallelism allows us to efficiently utilize the GPU resources and to perform tracking of the full human body at rates of 15 frames per second. the GPU achieves an average speedup of 7.5 over the CPU. For marker-less motion capture system consisting of four calibrated cameras, the computations were conducted on four CPU cores and four GTX GPUs on two cards.

关键词： graphics processing unit

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image retargeting using controlled shrinkage 12

Image retargeting using controlled shrinkage

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8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Pal, Rajarshi Mitra, Pabitra Mukherjee, Jayanta Institute for Development and Research in Banking Technology Hyderabad India Indian Institute of Technology Kharagpur India

ISBN: (纸本)9781450316606

the problem of retargeting a larger image in a small display is to maintain recognizability of the objects. the retargeting scheme proposed in this paper provides a suitable solution to this. the input image is partitioned into rectangular strips such that alternate strips contain important or unimportant objects. Each of these rectangular strips shrinks in size to fit the entire image into the small display. Strips containing unimportant objects shrink at a higher rate than those containing important objects. It is experimentally found that this scheme performs better than many existing schemes. An estimate for the range of values for shrinkage controlling parameters is also attempted here. © 2012 ACM.

关键词： Shrinkage

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Heritage app: Annotating images on mobile phones 12

Heritage app: Annotating images on mobile phones

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8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Panda, Jayaguru Sharma, Shashank Jawahar, C.V. IIIT-Hyderabad India

ISBN: (纸本)9781450316606

In this paper, we demonstrate a computer vision application on mobile phones. One can take a picture at a heritage site/monument and obtain associated annotations on a mid-end mobile phone instantly. this does not require any communication of images or features with a remote server, and all the necessary computations take place on the phone itself. We demonstrate the app on two indian heritage sites: Golkonda Fort and Hampi Temples. Underlying our application, we have a Bag of visual Words (BoW) image retrieval system, and an annotated database of images. In the process of developing this mobile app, we extend the performance, scope and applicability of computer vision techniques: (i) we do a BoW-based image retrieval on mobile phones from a database of 10K images within 50 MB of storage and 10 MB of RAM. (ii) we introduce a vocabulary pruning method for reducing the vocabulary size. (iii) we design a simple method of database pruning, that helps in reducing the size of the inverted index by removing semantically similar images. In (ii) and (iii), we demonstrate how memory(RAM) and computational speed can be optimized without any loss in performance. © 2012 ACM.

关键词： image retrieval

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