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Enhancing Visual Question Answering through Bi-Modal Feature Fusion: Performance Analysis 24

Enhancing Visual Question Answering through Bi-Modal Feature...

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6th International conference on image processing and Machine vision (IPMV)

作者： Mao, Keyu Fudan Univ Sch Data Sci Shanghai Peoples R China

ISBN: (纸本)9798400708473

With the significant development in deep learning within the domains of computer vision and natural language processing, the research involving the multimodal aspects of Visual Question Answering (VQA) has also reached a pivotal turning point in recent years. throughout prior investigations, scholars have consistently emphasized feature extraction from images and text. Numerous models have been applied in this context, ranging from the initial breakthroughs of Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN), to the momentary prominence of Dynamic Memory Networks, and subsequently, the rise of transformers in recent times. Nonetheless, it is imperative to recognize that beyond the ambit of feature extraction models, the fusion of bi-modal features assumes pivotal significance. this paper builds upon SOAT model from the previous work, serving as the baseline, and meticulously scrutinizes its performance across distinct fusion methodologies. Various notable fusion strategies, such as MUTAN and BLOCK, are considered. Notably, the most adept model achieves an impressive 65.74% accuracy on the VQA v2 dataset, outperforming established benchmarks. this outcome robustly substantiates the premise that fusion techniques exert tangible influence over the ultimate research outcomes.

关键词： VQA Natural language processing computer vision Fusion Bilinear models

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Bag of Visual Words based Correlation Filter Tracker (BoVW-CFT) 11

Bag of Visual Words based Correlation Filter Tracker (BoVW-C...

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

作者： Raju, Priya Mariam Mishra, Deepak Subrahmanyam, Gorthi Rama Krishna Sai Indian Inst Space Sci & Technol Thiruvananthapuram Kerala India Indian Inst Technol Tirupati Andhra Pradesh India

ISBN: (纸本)9781450366151

Accurate and robust visual object tracking is one of the most challenging computer vision problems. Recently, discriminative correlation filter trackers have shown promising results on benchmark datasets with continuous performance improvements in tracking accuracy and robustness. Still, these algorithms fail to track as the target object and background conditions undergo drastic changes over time. they are also incapable to resume tracking once the target is lost, limiting the ability to track long term. the proposed BoVW-CFT is a classifier-based generic technique to handle tracking uncertainties in correlation filter trackers. Tracking failures in correlation trackers are automatically identified and an image classifier with training, testing and online update stages is proposed as detector in the tracking scenario using Bag of VisualWords (BoVW) features. the proposed detector falls under the parts based model and is quite well suited in the tracking framework. Further, the online training stage in the proposed framework with updated model or training samples, incorporates temporal information, helping to detect rotated, blurred and scaled versions of the target. On detecting a target loss in the correlation tracker, the trained classifier, referred to as detector, is invoked to re-initialize the tracker with the actual target location. therefore, for each tracking uncertainty, two output patches are obtained, one each from the base tracker and the classifier. the final target location is estimated using the normalized cross-correlation with the initial target patch. the method has the advantages of mitigating the model drift in correlation trackers and learns a robust model that tracks long term. Extensive experimental results demonstrate an improvement of 4.1% in the expected overlap, 1.86% in accuracy and 15.46% in robustness on VOT2016 and 1.82% in overlap precision, 2.32% in AUC and 2.87% in success rates on OTB100.

关键词： Benchmarking

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Evaluation of Graph Layout Methods Based on Visual Perception 16

Evaluation of Graph Layout Methods Based on Visual Perceptio...

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

作者： Li, Jiafan Liu, Yuhua Wang, Changbo East China Normal Univ Sch Comp Sci & Software Engn Shanghai 200062 Peoples R China

ISBN: (纸本)9781450347532

Node-link diagrams provide an intuitive way to explore networks and have inspired a large number of automated graph layout strategies that optimize aesthetic criteria. However, any particular drawing approach cannot fully satisfy all these criteria simultaneously. So the evaluation methods are designed to explore the advantages and disadvantages of different graph layout methods from these standards. Starting from the point of visual perception, this paper analyzes the node's visual importance based on a user experiment and designs a model to measure the node's visual importance. then evaluate the pros and cons of graph layout methods by comparing the topological importance and visual importance of nodes. A heatmap-based visualization is used to provide visual feedback for the difference between the topological importance and visual importance of nodes. Meantime, a metric is built to quantify the difference precisely. Finally, experiments are done under different scale of data sets to further analyze the characteristics of these graph layout methods.

关键词： graph layout visual perception topological structure evaluation

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Zero-shot Learning using Graph Regularized Latent Discriminative Cross-domain Triplets 11

Zero-shot Learning using Graph Regularized Latent Discrimina...

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

作者： Gune, Omkar Vora, Meet Banerjee, Biplab Chaudhuri, Subhasis Indian Inst Technol Mumbai Maharashtra India Indian Inst Technol Roorkee Roorkee Uttar Pradesh India

ISBN: (纸本)9781450366151

Zero-shot learning (ZSL) for visual recognition aims at identifying the previously unseen class samples given a trained model on the labeled visual samples of seen classes and additional class-level semantic side information for all classes. Often ZSL is tackled by learning an embedding function from the visual to semantic space or vice-versa. However, learning this mapping often results in loss of discriminative property of learned embedding space, thus severely compromising the recognition performance on the test samples. In order to ensure improved discrimination in the embedding space, we introduce a ZSL framework by leveraging the intuitive idea of cross-domain triplets based metric learning for learning such a space. Additionally, we introduce a novel graph Laplacian based regularizer which aligns the graph structures of the visual and semantic spaces in the learned embedding space. Simultaneously optimizing both the criteria results in a compact, discriminative, and meaningful embedding space, which is experimentally found to be superior to most of its existing counterparts on both the standard ZSL (AwA and CUB) and the challenging generalized ZSL (AwA1, AwA2, CUB) settings.

关键词： Zero-shot learning cross-domain alignment

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Video Stabilization by Procrustes Analysis of Trajectories 16

Video Stabilization by Procrustes Analysis of Trajectories

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

作者： Jacob, Geethu Miriam Das, Sukhendu Indian Inst Technol Madras Tamil Nadu India

ISBN: (纸本)9781450347532

Video Stabilization algorithms are often necessary at the pre-processing stage for many applications in video analytics. the major challenges in video stabilization are the presence of jittery motion paths of a camera, large foreground moving objects with arbitrary motion and occlusions. In this paper, a simple, yet powerful video stabilization algorithm is proposed, by eliminating the trajectories with higher dynamism appearing due to jitter. A block-wise stabilization of the camera motion is performed, by analyzing the trajectories in Kendall's shape space. A 3-stage iterative process is proposed for each block of frames. At the first stage of the iterative process, the trajectories with relatively higher dynamism (estimated using optical flow) are eliminated. At the second stage, a Procrustes alignment is performed on the remaining trajectories and Frechet mean of the aligned trajectories is estimated. Finally, the Frechet mean is stabilized and a transformation of the stabilized Frechet mean to the original space (of the trajectories) yields the stabilized trajectories. A global optimization function has been designed for stabilization, thus minimizing wobbles and distortions in the frames. As the motion paths of the higher and lower dynamic regions become more distinct after stabilization, this iterative process helps in the identification of the stabilized background trajectories (with lower dynamism), which are used to warp the frames for rendering the stabilized frames. Experiments are done with varying levels of jitter introduced on stable videos, apart from a few benchmarked natural jittery videos. In cases, where synthetic jitter is fused on stable videos, an error norm comparing the groundtruth scores (scores of the stable videos) to the scores of the stabilized videos, is used for comparative study of performance. the results show the superiority of our proposed method over other state-of-the-art methods. [graphics] .

关键词： Kendall's shape space Procrustes Analysis Frechet Mean Video Stabilization Content Preserving Warps

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How empathizing with persona helps in design thinking: An experimental study with novice designers 12

How empathizing with persona helps in design thinking: An ex...

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12th International conference on Interfaces and Human computer Interaction 2018, 11th International conference on Game and Entertainment Technologies 2018 and 12th International conference on computer graphics, Visualization, computer vision and image processing 2018, part of the Multi conference on computer Science and Information Systems 2018, MCCSIS 2018

作者： Dahiya, Abhishek Kumar, Jyoti Indian Institute of Technology Delhi New Delhi India

ISBN: (纸本)9789898533791

Personas are widely used by HCI designers in design process. From defining target users to explicating user understanding, persona assists designers at various stages of design process of HCI systems. Design literature advocates the use of persona not only as a source of information about users but also as a tool to empathize. this paper reports observations from an experimental study done on novice designers on how empathizing with persona affected their design solutions. A total of 30 novice designers participated in this study. Participants were asked to design a graphical composition for persona. the data collected was analyzed through expert’s rating on design solutions on the basis of directness of illustration of persona information and verbal protocols. On the basis of direct illustration of persona information on design solutions it was observed that empathizing with persona helped designers to iterate more on design thinking. © 2018.

关键词： User centered design

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Event Recognition in Egocentric Videos Using a Novel Trajectory Based Feature 16

Event Recognition in Egocentric Videos Using a Novel Traject...

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

作者： Buddubariki, Vinodh Tulluri, Sunitha Gowd Mukherjee, Snehasis IIIT Chittoor Sricity India

ISBN: (纸本)9781450347532

this paper proposes an approach for event recognition in Egocentric videos using dense trajectories over Gradient Flow - Space Time Interest Point (GF-STIP) feature. We focus on recognizing events of diverse categories (including indoor and outdoor activities, sports and social activities and adventures) in egocentric videos. We introduce a dataset with diverse egocentric events, as all the existing egocentric activity recognition datasets consist of indoor videos only. the dataset introduced in this paper contains 102 videos with 9 different events (containing indoor and outdoor videos with varying lighting conditions). We extract Space Time Interest Points (STIP) from each frame of the video. the interest points are taken as the lead pixels and Gradient-Weighted Optical Flow (GWOF) features are calculated on the lead pixels by multiplying the optical flow measure and the magnitude of gradient at the pixel, to obtain the GF-STIP feature. We construct pose descriptors with the GF-STIP feature. We use the GF-STIP descriptors for recognizing events in egocentric videos with three different approaches: following a Bag of Words (BoW) model, implementing Fisher Vectors and obtaining dense trajectories for the videos. We show that the dense trajectory features based on the proposed GF-STIP descriptors enhance the efficacy of the event recognition system in egocentric videos.

关键词： GWOF Dense Trajectories Event Recognition First Person Egocentric

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An Extraction Method of Solid Line Graph Elements in Mathematical Graphs for Automating Translation of Tactile graphics

An Extraction Method of Solid Line Graph Elements in Mathema...

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6th International conference on Soft Computing and Intelligent Systems (SCIS) / 13th International Symposium on Advanced Intelligence Systems (ISIS)

作者： Chen, Jianjun Nagaya, Ryoji Takagi, Noboru Toyama Prefectural Univ Dept Intelligent Syst Design Engn Imizushi 9390398 Japan

ISBN: (纸本)9781467327435;9781467327428

Tactile graphics are images that use raised surface so that a visually impaired person can feel them. Tactile graphics are necessary to visually impaired students when they study mathematics and science. Since producing tactile graphics are not simple task, an intelligent computer-aided system for assisting the production of tactile graphics is needed. Mathematical graph recognition from printed materials plays an important role to develop such a system. So, this paper focuses on part of a method of mathematical graph recognition. A mathematical graph includes graph elements such as the rays representing the x-axis and the y-axis and the line segments or the curves representing functions or equations. Graph elements are often drawn so that they are overlapped each other. So, this paper discusses a method for extracting graph elements from an element which is drawn by overlapping more than one graph element. the effectiveness of our method is evaluated by a computer experiment.

关键词： tactile graphics graph recognition computer-aided systems image processing curve fitting

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Automatic pose estimation for range images on the GPU

Automatic pose estimation for range images on the GPU

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6th International conference on 3-D Digital Imaging and Modeling, 3DIM 2007

作者： Germann, Marcel In, Kyu Park Breitenstein, Michael D. Pfister, Hanspeter Zurich Switzerland Inha University Incheon Korea Republic of Zurich Switzerland Mitsubishi Electric Research Laboratories Cambridge MA United States

ISBN: (纸本)0769529399

Object pose (location and orientation) estimation is a common task in many computer vision applications. Although many methods exist, most algorithms need manual initialization and lack robustness to illumination variation, appearance change, and partial occlusions. We propose a fast method for automatic pose estimation without manual initialization based on shape matching of a 3D model to a range image of the scene. We developed a new error function to compare the input range image to pre-computed range maps of the 3D model. We use the tremendous dataparallel processing performance of modern graphics hardware to evaluate and minimize the error function on many range images in parallel. Our algorithm is simple and accurately estimates the pose of partially occluded objects in cluttered scenes in about one second. © 2007 IEEE.

关键词： graphics processing unit

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Regularized Random Walk Ranking for Co-Saliency Detection in images 11

Regularized Random Walk Ranking for Co-Saliency Detection in...

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

作者： Bardhan, Sayanti Jacob, Shibu Indian Inst Technol Madras Madras Tamil Nadu India Natl Inst Ocean Technol Madras Tamil Nadu India

ISBN: (纸本)9781450366151

Co-saliency detection refers to the computational process for identification of common but prominent and salient foreground regions in an image. However most of the co-saliency detection methods suffer from the following two limitations. First, co-saliency detection models largely generate superpixel level co-saliency maps that leads to sacrifice of significant information from the pixel level input images. Second, co-saliency detection frameworks mostly involve redesigned models for detection of co-salient objects in an image group, instead of utilization of the existing single image saliency detection models. To address these problems, we propose a novel framework, Co-saliency via Regularized Random Walk Ranking (CR2WR), which provides highly efficient pixel level co-saliency maps and utilizes existing saliency models on a single image to detect co-salient objects in an image sequence. this is achieved by: (1) Introducing Regularized random walk as the ranking function for a two-stage co-saliency detection framework. (2) Novel weighting function to incorporate more image information in graph construction and utilization of normalized Laplacian matrix for efficient cosaliency maps. (3) Generated saliency maps are fused further with high level priors namely, Location and Objectness priors, that enhances detection of co-salient regions. Suitably designed novel objective functions provide an enriched solution. the proposed model is evaluated on challenging benchmark co-saliency datasets. It is demonstrated that the proposed method outperforms prominent state-of-the-art methods in terms of efficiency and computational time.

关键词： Computational efficiency

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