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检索条件"任意字段=10th Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2016"

共 143 条记录，以下是21-30 订阅

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Generating Synthetic Handwriting using n-gram letter glyphs 16

Generating Synthetic Handwriting using n-gram letter glyphs

引用

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

作者： Dey, Arka Ujjal Harit, Gaurav Indian Inst Technol Jodhpur Old Residency Rd Jodhpur Rajasthan India

ISBN: (纸本)9781450347532

We propose a framework for synthesis of natural semi cursive handwritten Latin script that can find application in text personalization, or in generation of synthetic data for recognition systems. Our method is based on the generation of synthetic n-gram letter glyphs and their subsequent concatenation. We propose a non-parametric data driven generation scheme that is able to mimic the variation observed in handwritten glyph samples to synthesize natural looking synthetic glyphs. these synthetic glyphs are then stitched together to form complete words, using a spline based concatenation scheme. Further, as a refinement, our method is able to generate pen-lifts, giving our results a natural semi cursive look. through subjective experiments and detailed analysis of the results, we demonstrate the effectiveness of our formulation in being able to generate natural looking synthetic script.

关键词： HandWriting Synthesis Gaussian Process n-gram

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On the (Soccer) Ball 16

On The (Soccer) Ball

引用

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

作者： Sanyal, Samriddha Kundu, Arnab Mukherjee, Dipti Prasad Indian Stat Inst 203 Barrackpore Trunk Rd Kolkata 700108 India

ISBN: (纸本)9781450347532

the problem of tracking ball in a soccer video is challenging because of sudden change in speed and orientation of the soccer ball. Successful tracking in such a scenario depends on the ability of the algorithm to balance prior constraints continuously against the evidence garnered from the sequences of images. this paper proposes a particle filter based algorithm that tracks the ball when it changes its direction suddenly or takes high speed. Exact, deterministic tracking algorithms based on discretized functional, suffer from severe limitations in the form of prior constraints. Our tracking algorithm has shown excellent result even for partial occlusion which is a major concern in soccer video. We have shown that the proposed tracking algorithm is at least 7.2% better compared to competing approaches for soccer ball tracking.

关键词： Tracking Soccer ball Particle filter Measurement space Resampling

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Multi-slice Tomographic Reconstruction: To Couple or Not to Couple 16

Multi-slice Tomographic Reconstruction: To Couple or Not to ...

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

作者： Gopal, Preeti Chandran, Sharat Svalbe, Imants Rajwade, Ajit Indian Inst Technol Dept Comp ViGIL Bombay Maharashtra India IITB Monash Res Acad Bombay Maharashtra India Monash Univ Dept Phys & Astron Clayton Vic Australia

ISBN: (纸本)9781450347532

Recent work in tomography focuses on algorithms that enable faster and more accurate reconstruction from as few measurements as possible. We review the advantage of jointly reconstructing multiple slices and show that joint reconstruction may suffer in the presence of adjacent dissimilar slices. this gives rise to the need to detect similarity or dissimilarity of unknown images before performing joint reconstruction. We propose a method to detect 'similar' slices directly from their tomographic measurements and juxtapose these similar slices. Since the images themselves are not available by definition, we compute similarity between slices based on image moments;these in turn are estimated in a novel way from Radon projection moments. A segmented least squares algorithm is then designed to couple only similar slices. Our results confirm the benefit of this method for tomographic reconstruction.

关键词： Compressive sensing Radon projection moments image moments tomographic reconstruction

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Event Geo-Localization and Tracking From Crowd-Sourced Video Metadata 16

Event Geo-Localization and Tracking From Crowd-Sourced Video...

引用

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

作者： More, Amit Chaudhuri, Subhasis Indian Inst Technol Dept Elect Engn Bombay Maharashtra India

ISBN: (纸本)9781450347532

We propose a novel technique for event geo-localization (i.e. 2-D location of the event on the surface of the earth) from the sensor metadata of crowd-sourced videos collected from smartphone devices. With the help of sensors available in the smartphone devices, such as digital compass and GPS receiver, we collect metadata information such as camera viewing direction and location along with the video. the event localization is then posed as a constrained optimization problem using available sensor metadata. Our results on the collected experimental data shows correct localization of events, which is particularly challenging for classical vision based methods because of the nature of the visual data. Since we only use sensor metadata in our approach, computational overhead is much less compared to what would be if video information is used. At the end, we illustrate the benefits of our work in analyzing the video data from multiple sources through geo-localization.

关键词： Event localization Smartphone Digital Compass Optimization GPS

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Deep image Inpainting with Region Prediction at Hierarchical Scales 16

Deep Image Inpainting with Region Prediction at Hierarchical...

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

作者： Chakraborty, Souradeep Kundu, Jogendra Nath Babu, R. Venkatesh Indian Inst Sci Dept Computat & Data Sci Bangalore Karnataka India

ISBN: (纸本)9781450347532

In this paper, we propose a CNN based method for image inpainting, which utilizes the inpaintings generated at different hierarchical resolutions. Firstly, we begin with the prediction of the missing image region with larger contextual information at the lowest resolution using deconv layers. Next, we refine the predicted region at greater hierarchical scales by imposing gradually reduced contextual information surrounding the predicted region by training different CNNs. thus, our method not only utilizes information from different hierarchical resolutions but also intelligently leverages the context information at different hierarchy to produce better inpainted image. the individual models are trained jointly, using loss functions placed at intermediate layers. Finally, the CNN generated image region is sharpened using the unsharp masking operation, followed by intensity matching with the contextual region, to produce visually consistent and appealing inpaintings with more prominent edges. Comparison of our method with well-known inpainting methods, on the Caltech 101 objects dataset, demonstrates the quantitative and qualitative strengths of our method over the others.

关键词： image inpainting context hierarchical scales image sharpening intensity matching

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Reinforced Random Forest 16

Reinforced Random Forest

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

作者： Paul, Angshuman Mukherjee, Dipti Prasad Indian Stat Inst 203 BT Rd Kolkata India

ISBN: (纸本)9781450347532

Reinforcement learning improves classification accuracy. But use of reinforcement learning is relatively unexplored in case of random forest classifier. We propose a reinforced random forest (RRF) classifier that exploits reinforcement learning to improve classification accuracy. Our algorithm is initialized with a forest. then the entire training data is tested using the initial forest. In order to reinforce learning, we use mis-classified data points to grow certain number of new trees. A subset of the new trees is added to the existing forest using a novel graph-based approach. We show that addition of these trees ensures improvement in classification accuracy. this process is continued iteratively until classification accuracy saturates. the proposed RRF has low computational burden. We achieve at least 3% improvement in F-measure compared to random forest in three breast cancer datasets. Results on benchmark datasets show significant reduction in average classification error.

关键词： Random forest reinforcement learning classification accuracy shortest path

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Detection and Segmentation of Mirror-like Surfaces Using Structured Illumination 16

Detection and Segmentation of Mirror-like Surfaces Using Str...

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

作者： Aggarwal, Rajat Namboodiri, Anoop M. Int Inst Informat Technol Hyderabad Kohli Ctr Intelligent Syst Hyderabad Andhra Pradesh India

ISBN: (纸本)9781450347532

In computer vision, many active illumination techniques employ Projector-Camera systems to extract useful information from the scenes. Known illumination patterns are projected onto the scene and their deformations in the captured images are then analyzed. We observe that the local frequencies in the captured pattern for the mirror-like surfaces is different from the projected pattern. this property allows us to design a custom Projector-Camera system to segment mirror-like surfaces by analyzing the local frequencies in the captured images. the system projects a sinusoidal pattern and capture the images from projector's point of view. We present segmentation results for the scenes including multiple reflections and inter-reflections from the mirror-like surfaces. the method can further be used in the separation of direct and global components for the mirror-like surfaces by illuminating the non-mirror-like objects separately. We show how our method is also useful for accurate estimation of shape of the non-mirror-like regions in the presence of mirror-like regions in a scene.

关键词： Structured Illumination Mirror-like surfaces Segmentation Projector- Camera

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Informed Multimodal Latent Subspace Learning via Supervised Matrix Factorization 16

Informed Multimodal Latent Subspace Learning via Supervised ...

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

作者： Gaurav, Ramashish Verma, Mridula Shukla, K. K. BHU Indian Inst Technol Varanasi Uttar Pradesh India

ISBN: (纸本)9781450347532

Matrix factorization technique has been widely used as a popular method to learn a joint latent-compact subspace, when multiple views or modals of objects (belonging to single-domain or multiple-domain) are available. Our work confronts the problem of learning an informative latent subspace by imparting supervision to matrix factorization for fusing multiple modals of objects, where we devise simpler supervised additive updates instead of multiplicative updates, thus scalable to large scale datasets. To increase the classification accuracy we integrate the label information of images with the process of learning a semantically enhanced subspace. We perform extensive experiments on two publicly available standard image datasets of NUS WIDE and compare the results with state-of-the-art subspace learning and fusion techniques to evaluate the efficacy of our framework. Improvement obtained in the classification accuracy confirms the effectiveness of our approach. In essence, we propose a novel method for supervised data fusion thus leading to supervised subspace learning.

关键词： image Classification Joint Subspace Learning Supervised Matrix Factorization

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Data-driven 2D Effects Animation 16

Data-driven 2D Effects Animation

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

作者： Grover, Divyanshu Chaudhuri, Parag Indian Inst Technol Dept Comp Sci & Engn Bombay 400076 Maharashtra India

ISBN: (纸本)9781450347532

Making plausible, high quality visual effects, like water splashes or fire, in traditional 2D animation pipelines require an animator to draw many frames of phenomena that are very difficult to recreate manually. We present a technique that uses a database of video clips of such phenomena to assist the animator. the animator has to only input sample sketched frames of the phenomena at particular time instants. these are matched to frames of the video clips and a plausible sequence of frames is generated from these clips that contain the animator drawn frames as constraints. the colour style of the hand-drawn frames is used to render the generated frames, thus resulting in a 2D animation that follows the style and intent of the 2D animator. Our system can also create multi-layered effects animation, allowing the animator to draw interacting mixed phenomena, like water being poured on fire.

关键词： non-photorealistic animation non-photorealistic rendering sketch-based special effects

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Towards Semantic Visual Representation: Augmenting image Representation with Natural Language Descriptors 16

Towards Semantic Visual Representation: Augmenting Image Rep...

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

作者： Mopuri, Konda Reddy Babu, R. Venkatesh Indian Inst Sci Bangalore Karnataka India

ISBN: (纸本)9781450347532

Learning image representations has been an interesting and challenging problem. When users upload images to photo sharing websites, they often provide multiple textual tags for ease of reference. these tags can reveal significant information about the content of the image such as the objects present in the image or the action that is taking place. Approaches have been proposed to extract additional information from these tags in order to augment the visual cues and build a multi-modal image representation. However, the existing approaches do not pay much attention to the semantic meaning of the tags while they encode. In this work, we attempt to enrich the image representation with the tag encodings that leverage their semantics. Our approach utilizes neural network based natural language descriptors to represent the tag information. By complementing the visual features learned by convnets, our approach results in an efficient multi-modal image representation. Experimental evaluation suggests that our approach results in a better multi-modal image representation by exploiting the two data modalities for classification on benchmark datasets.

关键词： Multi-modal image representation neural embeddings natural language descriptors word2vec text encoding image description

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