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6th International Work-conference on the Interplay Between Natural and Artificial Computation (IWINAC)

作者： Sanchez, Jose L. Viana, Raul Lopez, Maria T. Fernandez-Caballero, Antonio Univ Castilla La Mancha Inst Invest Informat Albacete Albacete 02071 Spain Univ Castilla La Mancha Dept Sistemas Informat Albacete 02071 Spain

ISBN: (纸本)9783319597737;9783319597720

computer vision is a great interest field offering relevant information in a wide variety of areas. Different video processing techniques, for instance, allow us to detect moving objects from image sequences of fixed surveillance cameras. Lateral Interaction in Accumulative Computation is a classical bio-inspired method that is usually applied for detecting moving objects in video processing. this method achieves high precision but also requires a high processing time. this paper introduces a parallel code capable of keeping a high performance in terms of accuracy and runtime for the method. For some of the image sequences tested, a speed-up of 67x over the sequential counterpart is achieved.

关键词： Motion detection Acceleration graphics processing Unit Lateral Interaction in Accumulative Computation

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computer vision and image processing 1

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丛书名： Communications in computer and Information Science

1000年

作者： Satish Kumar Singh P. Nagabhushan Partha Roy Balasubramanian Raman

ISBN: (数字)9789811610929

ISBN: (纸本)9789811610912

this three-volume set (CCIS 1367-1368) constitutes the refereed proceedings of the 5th International conference on computer vision and image processing, CVIP 2020, held in Prayagraj, India, in December 2020. Due to the COVID-19 pandemic the conference was partially held online.;the 134 papers papers were carefully reviewed and selected from 352 submissions. the papers present recent research on such topics as biometrics, forensics, content protection, image enhancement/super-resolution/restoration, motion and tracking, image or video retrieval, image, image/video processing for autonomous vehicles, video scene understanding, human-computer interaction, document image analysis, face, iris, emotion, sign language and gesture recognition, 3D image/video processing, action and event detection/recognition, medical image and video analysis, vision-based human GAIT analysis, remote sensing, and more.

关键词： computer Imaging, vision, Pattern Recognition and graphics Machine Learning computer Systems Organization and Communication Networks computers and Education computer Applications

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computer vision and image processing 1

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丛书名： Communications in computer and Information Science

1000年

作者： Satish Kumar Singh P. Nagabhushan Partha Roy Balasubramanian Raman

ISBN: (数字)9789811611032

ISBN: (纸本)9789811611025

关键词： computer Imaging, vision, Pattern Recognition and graphics Artificial Intelligence Information Systems and Communication Service Computing Milieux computer System Implementation computer Appl. in Social and Behavioral Sciences

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Feature extraction and iconic visualization

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IEEE TRANSACTIONS ON VISUALIZATION AND computer graphics 1996年第2期2卷 111-119页

作者： vanWalsum, T Post, FH Silver, D Post, FJ DELFT UNIV TECHNOL FAC TECH MATH & INFORMAT NL-2628 BL DELFT NETHERLANDS RUTGERS STATE UNIV DEPT ELECT & COMP ENGN PISCATAWAY NJ 08855 USA

We present a conceptual framework acid a process model for feature extraction and iconic visualization. the features are regions of interest extracted from a dataset: they are represented by attribute sets, which play a key role in the visualization process. these attribute sets are mapped to icons, or symbolic parametric objects, for visualization. the features provide a compact abstraction of the original data, and the icons are a natural way to visualize them. We present generic techniques to extract features and to calculate attribute sets, and describe a simple but powerful modeling language which was developed to create icons and to link the attributes to the icon parameters. We present illustrative examples of iconic Visualization created with the techniques described, showing the effectiveness of this approach.

关键词： Feature Extraction Graphical User Interfaces Data Visualisation Visual Languages Feature Extraction Iconic Visualization Conceptual Framework Process Model Dataset Attribute Sets Visualization Process Symbolic Parametric Objects Compact Abstraction Generic Techniques Modeling Language Icon Parameters Feature Extraction Data Visualization Data Mining computer Society Silver Geometry Laboratories image processing Radiology Mathematics

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Semantic multinomial representation for scene images using CNN-based pseudo-concepts and concept neural network 6th

Semantic multinomial representation for scene images using C...

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6th National conference on computer vision, Pattern Recognition, image processing and graphics, NCVPRIPG 2017

作者： Pradhan, Deepak Kumar Gupta, Shikha thenkanidiyoor, Veena Aroor Dinesh, Dileep Department of Computer Science and Engineering National Institute of Technology Goa PondaGoa401403 India School of Computing and Electrical Engineering Indian Institute of Technology Mandi MandiH.P.175001 India

ISBN: (纸本)9789811300196

For challenging visual recognition tasks such as scene classification and object detection there is a need to bridge the semantic gap between low-level features and the semantic concept descriptors. this requires mapping a scene image onto a semantic representation. Semantic multinomial (SMN) representation is a semantic representation of an image that corresponds to a vector of posterior probabilities of concepts. In this work we propose to build a concept neural network (CoNN) to obtain the SMN representation for a scene image. An important issue in building a CoNN is that it requires the availability of ground truth concept labels. In this work we propose to use pseudo-concepts obtained from feature maps of higher level layers of convolutional neural network. the effectiveness of the proposed approaches are studied using standard datasets. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Semantics

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Real Time Hand Gesture Recognition for Human computer Interaction 6

Real Time Hand Gesture Recognition for Human Computer Intera...

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IEEE 6th International Advance Computing conference (IACC)

作者： Agrawal, Rishabh Gupta, Nikita Savitribai Phule Pune Univ Dept Comp Engn Army Inst Technol Pune Maharashtra India

ISBN: (纸本)9781467382861

Most of the human computer interaction interfaces that are designed today require explicit instructions from the user in the form of keyboard taps or mouse clicks. As the complexity of these devices increase, the sheer amount of such instructions can easily disrupt, distract and overwhelm users. A novel method to recognize hand gestures for human computer interaction, using computer vision and image processing techniques, is proposed in this paper. the proposed method can successfully replace such devices (e.g. keyboard or mouse) needed for interacting with a personal computer. the method uses a commercial depth + rgb camera called Senz3D, which is cheap and easy to buy as compared to other depth cameras. the proposed method works by analyzing 3D data in real time and uses a set of classification rules to classify the number of convexity defects into gesture classes. this results in real time performance and negates the requirement of any training data. the proposed method achieves commendable performance with very low processor utilization.

关键词： Human computer Interaction (HCI) gesture recognition hand gestures convex hull convexity defects computer vision and image processing

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A dynamic interface adaptation approach for accessible immersive environments

A dynamic interface adaptation approach for accessible immer...

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2016 International conference on Interfaces and Human computer Interaction, IHCI 2016, Game and Entertainment Technologies, GET 2016 and computer graphics, Visualization, computer vision and image processing, CGVCVIP 2016

作者： Paliokas, Ioannis Segkouli, Sofia Tzovaras, Dimitrios Karagiannidis, Charalampos Information Technologies Institute-ITI Centre for Research and Technology Hellas-CERTH 6th km Charilaou-Thermi Rd P.O. Box 60361 Thermi ThessalonikiGR 57001 Greece Department of Special Education University of Thessaly Argonafton and Filellinon Volos Greece

ISBN: (纸本)9789898533524

Current trends in context-Aware computing have altered the static nature of interfaces and equipped them with the ability to adapt to the physical or social context. this paper investigates new paradigms towards cognitive context-Awareness which relies on adaptation and personalization factors of more explicit interfaces oriented by individuals' cognitive processes. the main objective is to propose a smooth transition from existing interface design practices to advanced adaptation techniques concerning interfaces' design, based on cognitive abilities' inclination. To prove this, a group of young users, elderly and MCI positives, were asked to perform series of common tasks in a Metaverse interface design. A prediction model was developed to categorize users based on the way they interact with the interface. the outcomes of the interaction pattern analysis serve as the criterion based on which the proposed novel interaction-Aware interface can adapt users' abilities to maximize accessibility and comfort.

关键词： Design

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A digital presenter with behaviour

A digital presenter with behaviour

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6th IASTED International conference on Signal and image processing

作者： Lee, JH Lee, IH Elect & Telecommun Res Inst Digital Content Res Div Taejon 305350 South Korea

ISBN: (纸本)0889864349

computer graphics is developing day by day, and computer animation with 3D virtual character becomes usual. As this character animation is especially focused on humanoid and has fascinating factor, it is used in the variety of fields. Existing presentations for user were mostly video-based or web-based applications and it is rare to use 3D character, because of the difficulty in character animation. In this paper, we propose a digital presenter with behaviour. Our digital presenter is 3D character with animation, and presents something instead of human presenter. To make animation faster and more real, we try to add the behaviour to digital presenter's animation.

关键词： computer graphics virtual reality character animation simulation digital presenter behaviour

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Nrityantar: Pose oblivious indian classical dance sequence classification system 11

Nrityantar: Pose oblivious Indian classical dance sequence c...

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

作者： Kaushik, Vinay Mukherjee, Prerana Lall, Brejesh IIT Delhi Dept Elect Engn Delhi India

ISBN: (纸本)9781450366151

In this paper, we attempt to advance the research work done in human action recognition to a rather specialized application namely indian Classical Dance (ICD) classification. the variation in such dance forms in terms of hand and body postures, facial expressions or emotions and head orientation makes pose estimation an extremely challenging task. To circumvent this problem, we construct a pose-oblivious shape signature which is fed to a sequence learning framework. the pose signature representation is done in two-fold process. First, we represent person-pose in first frame of a dance video using symmetric Spatial Transformer Networks (STN) to extract good person object proposals and CNNb-ased parallel single person pose estimator (SPPE). Next, the pose basis are converted to pose flows by assigning a similarity score between successive poses followed by non-maximal suppression. Instead of feeding a simple chain of joints in the sequence learner which generally hinders the network performance we constitute a feature vector of the normalized distance vectors, flow, angles between anchor joints which captures the adjacency configuration in the skeletal pattern. thus, the kinematic relationship amongst the body joints across the frames using pose estimation helps in better establishing the spatio-temporal dependencies. We present an exhaustive empirical evaluation of state-of-the-art deep network based methods for dance classification on ICD dataset.

关键词： Pose Signature Dance classification Action Recognition Motion and Video Analysis Deep Learning Supervised Learning LSTM

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Epipolar Geometry based Learning of Multi-view Depth and Ego-Motion from Monocular Sequences 11

Epipolar Geometry based Learning of Multi-view Depth and Ego...

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

作者： Prasad, Vignesh Das, Dipanjan Bhowmick, Brojeshwar TCS Res & Amp Innovat Embedded Syst & Amp Robot Kolkata India

ISBN: (纸本)9781450366151

Deep approaches to predict monocular depth and ego-motion have grown in recent years due to their ability to produce dense depth from monocular images. the main idea behind them is to optimize the photometric consistency over image sequences by warping one view into another, similar to direct visual odometry methods. One major drawback is that these methods infer depth from a single view, which might not effectively capture the relation between pixels. Moreover, simply minimizing the photometric loss does not ensure proper pixel correspondences, which is a key factor for accurate depth and pose estimations. In contrast, we propose a 2-view depth network to infer the scene depth from consecutive frames, thereby learning inter-pixel relationships. To ensure better correspondences, thereby better geometric understanding, we propose incorporating epipolar constraints to make the learning more geometrically sound. We use the Essential matrix obtained using Nister's Five Point Algorithm, to enforce meaningful geometric constraints, rather than using it as training labels. this allows us to use lesser no. of trainable parameters compared to state-of-the-art methods. the proposed method results in better depth images and pose estimates, which capture the scene structure and motion in a better way. Such a geometrically constrained learning performs successfully even in cases where simply minimizing the photometric error would fail.

关键词： Monocular Depth Visual Odometry Epipolar Geometry computer vision Unsupervised Learning

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