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arXiv 2021年

作者： Li, Yuanzhuo Zheng, Yunan Chen, Jie Xu, Zhenyu Liu, Yiguang Vision and Image Processing Lab School of Computer Science Sichuan University China

Among the major remaining challenges for single image super resolution (SISR) is the capacity to recover coherent images with global shapes and local details conforming to human vision system. Recent generative adversarial network (GAN) based SISR methods have yielded overall realistic SR images, however, there are always unpleasant textures accompanied with structural distortions in local regions. To target these issues, we introduce the gradient branch into the generator to preserve structural information by restoring high-resolution gradient maps in SR process. In addition, we utilize a U-net based discriminator to consider both the whole image and the detailed per-pixel authenticity, which could encourage the generator to maintain overall coherence of the reconstructed images. Moreover, we have studied objective functions and LPIPS perceptual loss is added to generate more realistic and natural details. Experimental results show that our proposed method outperforms state-of-the-art perceptual-driven SR methods in perception index (PI), and obtains more geometrically consistent and visually pleasing textures in natural image restoration. © 2021, CC BY.

关键词： Generative adversarial networks

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Quantization in Relative Gradient Angle Domain For Building Polygon Estimation

Quantization in Relative Gradient Angle Domain For Building ...

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International Conference on Pattern Recognition

作者： Yuhao Chen Yifan Wu Linlin Xu Alexander Wong Vision and Image Processing Lab (VIP) University of Waterloo Waterloo Ontario Canada

Building footprint extraction in remote sensing data benefits many important applications, such as urban planning and population estimation. Recently, rapid development of convolutional neural networks (CNNs) and open-sourced high resolution satellite building image datasets have pushed the performance boundary further for automated building extractions. However, CNN approaches often generate imprecise building morphologies including noisy edges and round corners. In this paper, we leverage the performance of CNNs, and propose a module that uses prior knowledge of building corners to create angular and concise building polygons from CNN segmentation outputs. We describe a new transform, Relative Gradient Angle Transform (RGA Transform) that converts object contours from time vs. space to time vs. angle. We propose a new shape descriptor, Boundary Orientation Relation Set (BORS), to describe angle relationship between edges in RGA domain, such as orthogonality and parallelism. Finally, we develop an energy minimization framework that makes use of the angle relationship in BORS to straighten edges and reconstruct sharp corners, and the resulting corners create a polygon. Experimental results demonstrate that our method refines CNN output from a rounded approximation to a more clear-cut angular shape of the building footprint.

关键词： Shape Buildings Urban planning Sociology Estimation Transforms Minimization

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BIORTHOGONAL WAVELET TRANSFORM BASED image FUSION USING ABSOLUTE MAXIMUM FUSION RULE

BIORTHOGONAL WAVELET TRANSFORM BASED IMAGE FUSION USING ABSO...

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IEEE Conference on Information & Communication Technologies

作者： Om Prakash Richa Srivastava Ashish Khare Image Processing and Computer Vision Lab Department of Electronics and Communication University of Allahabad

ISBN: (纸本)9781467357593

The objective of image fusion is to combine relevant information from two or more images of the same scene into a single composite image which is more informative and is more suitable for human and machine perception. In recent past, different methods of image fusion have been proposed in literature both in spatial domain and wavelet domain. Spatial domain based methods produce spatial distortions in the fused image. Spatial domain distortion can be well handled by the use of wavelet transform based image fusion methods. In this paper, we propose a pixel-level image fusion scheme using multiresolution Biorthogonal wavelet transform (BWT). Wavelet coefficients at different decomposion levels are fused using absolute maximum fusion rule. Two important properties wavelet symmetry and linear phase of BWT have been exploited for image fusion because they are capable to preserve edge information and hence reducing the distortions in the fused image. The performance of the proposed method have been extensively tested on several pairs of multifocus and multimodal images both free from any noise and in presence of additive white Gaussian noise and compared visually and quantitatively against existing spatial domain methods. Experimental results show that the proposed method improves fusion quality by reducing loss of significant information available in individual images. Fusion factor, entropy and standard deviation are used as quantitative quality measures of the fused image.

关键词： image fusion Multifocus images Multimodality Biorthogonal wavelet transform Fusion rules

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Ensemble-based Learning Using Few Training Samples for Video Surveillance Scenarios

Ensemble-based Learning Using Few Training Samples for Video...

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International Conference on image processing Theory, Tools and Applications

作者： C. A. Mitrea S. Carata B. Ionescu T. Piatrik M. Ghenescu Softrust Vision Analytics UTI Grup Image Processing and Analysis Lab UPB Multimedia and Vision Group QMUL

ISBN: (纸本)9781479986385

The article targets the task of content-based multiple-instance people retrieval from video surveillance footage. This task is particularly challenging when applied on such datasets as the available samples to train the decisioning system and formulate the query are insufficient (one image, few frames, or seconds of video recording). To cope with these challenges we investigate three established ensemble-based learning techniques, e.g., boosting, bagging and blending (stacking). Such methods are based on a set of procedures employed to train multiple learning algorithms and combine their outputs, while functioning together as a unified system of decision making. The approach was evaluated on two standard datasets (accounting for 16 people searching scenario on ca. 53000 labeled frames). Performance in terms of F2-Score attained promising results while dealing with our current task.

关键词： Reduced training samples Ensemble learning Classification Multiple instance retrieval Video Surveillance video monitoring current task Video Recording Dataset Blending

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On stabilisation of parametric active contours

On stabilisation of parametric active contours

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2007 IEEE Computer Society Conference on Computer vision and Pattern Recognition, CVPR'07

作者： Srikrishnan, V. Chaudhuri, Subhasis Roy, Sumantra Dutta Ševčovič, Daniel Vision and Image Processing Lab. EE Dept. I.I.T Bombay Mumbai India Dept. of Applied Math and Stats. Comenius University Bratislava Slovakia

ISBN: (纸本)1424411807

Parametric active contours have been used extensively in computer vision for different tasks like segmentation and tracking. However, all parametric contours are known to suffer from the problem of frequent bunching and spacing out of curve points locally during the curve evolution. In a spline based implementation of active contours, this leads to occasional formation of loops locally, and subsequently the curve blows up due to instabilities. It has been shown earlier that in addition to usual evolution along the normal direction, the curve should also be evolved in the tangential direction for stability purposes. In this paper, we provide a mathematical basis for selecting such a suitable tangential component for stabilisation. We prove the boundedness of the evolved curve in this paper, and provide the physical significance. We demonstrate the usefulness of the proposed method with a number of experiments. ©2007 IEEE.

关键词： Contour measurement

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LICENSE PLATE LOCALIZATION BASED ON EDGE-GEOMETRICAL FEATURES USING MORPHOLOGICAL APPROACH

LICENSE PLATE LOCALIZATION BASED ON EDGE-GEOMETRICAL FEATURE...

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IEEE International Conference on image processing

作者： Jinn-Li Tan Syed A.R Abu-Bakar Musa M. Mokji Computer Vision Video and Image Processing Lab ECE Department Universiti Teknologi Malaysia

ISBN: (纸本)9781479923427

Malaysian car plates in general appear in different character styles, types (either single or double row), sizes, spacing and character counts. Such variations cause even detecting and localizing these plates a difficult problem. The problem of localization is aggravated further during night time due to poor illumination. In this paper, we introduce the idea of edgegeometrical features in detecting these plates. The edge part is obtained from the use of Difference of Gaussian operation followed by Sobel vertical edge mask. Prior to that, gamma correction is applied to increase the detection of edges. We then apply morphological operations to get the plate region candidates. Using these regions, together with the edge image, we calculate geometrical features of these regions and use rule-based classifier to correctly identify the true plate region. Finally, we test out method using our own data set which contained 250 images captured during day time and 100 images captured during night time. The result of the proposed method shows 96.9% success rate.

关键词： Gamma correction Difference of Gaussian Sobel vertical mask Rule-based classifier Bone Plate PLATES edge image plate Licence Plates Edge detection Morphological operations double-row

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EXTERNAL FORCES FOR ACTIVE CONTOURS USING THE UNDECIMATED WAVELET TRANSFORM

EXTERNAL FORCES FOR ACTIVE CONTOURS USING THE UNDECIMATED WA...

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IEEE International Conference on image processing

作者： Ahmed Gawish Paul Fieguth Vision and Image Processing (VIP) Lab Department of Systems Design Engineering University of Waterloo

ISBN: (纸本)9781479983407

A limitation of active contours models (both parametric and geometric) is their sensitivity to noise. Many solutions to noise sensitivity have been proposed in the literature, with the current state-of-the-art based on image blurring and multiresolution processing. However a significant drawback of both approaches is the side effect of edge delocalization. In this paper, gradient information extracted from all resolutions of the undecimated wavelet transform is used to build the external force map for the active contour. The new map accurately drives the active contour and improves edge localization. The proposed method builds on both Gradient Vector Flow and Vector Field Convolution active contours. Comparisons to classical and state-of-the-art methods show a dramatic improvement in active contour convergence for all levels of noise.

关键词： Active contours Undecimated wavelet transform Active contours contour image blur Noise sensitivity Side Effect wavelet transforms Gradient vector Noise Parametric

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NutritionVerse-Thin: An Optimized Strategy for Enabling Improved Rendering of 3D Thin Food Models

arXiv

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arXiv 2023年

作者： Tai, Chi-En Amy Li, Jason Kumar, Sriram Nair, Saeejith Chen, Yuhao Xi, Pengcheng Wong, Alexander Vision and Image Processing Lab University of Waterloo Canada National Research Council Canada

With the growth in capabilities of generative models, there has been growing interest in using photo-realistic renders of common 3D food items to improve downstream tasks such as food printing, nutrition prediction, or management of food wastage. Despite 3D modelling capabilities being more accessible than ever due to the success of NeRF based view-synthesis, such rendering methods still struggle to correctly capture thin food objects, often generating meshes with significant holes. In this study, we present an optimized strategy for enabling improved rendering of thin 3D food models, and demonstrate qualitative improvements in rendering quality. Our method generates the 3D model mesh via a proposed thin-object-optimized differentiable reconstruction method and tailors the strategy at both the data collection and training stages to better handle thin objects. While simple, we find that this technique can be employed for quick and highly consistent capturing of thin 3D objects. Copyright © 2023, The Authors. All rights reserved.

关键词： 3D modeling

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How Much You Ate? Food Portion Estimation on Spoons

arXiv

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arXiv 2024年

作者： Sharma, Aaryam Czarnecki, Chris Chen, Yuhao Xi, Pengcheng Xu, Linlin Wong, Alexander Vision and Image Processing Lab University of Waterloo Canada National Research Council Canada

Monitoring dietary intake is a crucial aspect of promoting healthy living. In recent years, advances in computer vision technology have facilitated dietary intake monitoring through the use of images and depth cameras. However, the current state-of-the-art image-based food portion estimation algorithms assume that users take images of their meals one or two times, which can be inconvenient and fail to capture food items that are not visible from a top-down perspective, such as ingredients submerged in a stew. To address these limitations, we introduce an innovative solution that utilizes stationary user-facing cameras to track food items on utensils, not requiring any change of camera perspective after installation. The shallow depth of utensils provides a more favorable angle for capturing food items, and tracking them on the utensil’s surface offers a significantly more accurate estimation of dietary intake without the need for post-meal image capture. The system is reliable for estimation of nutritional content of liquid-solid heterogeneous mixtures such as soups and stews. Through a series of experiments, we demonstrate the exceptional potential of our method as a non-invasive, user-friendly, and highly accurate dietary intake monitoring tool. © 2024, CC BY.

关键词： Cameras

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HIGH DYNAMIC RANGE MAP ESTIMATION VIA FULLY CONNECTED RANDOM FIELDS WITH STOCHASTIC CLIQUES

HIGH DYNAMIC RANGE MAP ESTIMATION VIA FULLY CONNECTED RANDOM...

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IEEE International Conference on image processing

作者： F. Y. Li M. J. Shafiee A. G. Chung B. Chwyl F. Kazemzadeh A. Wong J. Zelek Vision & Image Processing Lab Systems Design Engineering Dept. University of Waterloo

ISBN: (纸本)9781479983407

The reconstruction of high dynamic range (HDR) images via conventional camera systems and low dynamic range (LDR) images is a growing field of research in image acquisition. The radiance map associated with the HDR image of a scene is typically computed using multiple images of the same scene captured at different exposures (i.e., bracketed LDR imzages). This approach, though inexpensive, is sensitive to noise under high camera ISO. Each bracketed image is associated with a different level of noise due to the change in exposure time, and the noise is further amplified when tone-mapping the HDR image for display. A new framework is proposed to address the associated noise in the context of random fields. The estimation of the HDR image from a set of LDR images is formulated as a stochastically fully connected conditional random field where the spatial information is incorporated to compute the HDR value in combination with the LDR image values. Experimental results show that the proposed framework compensated the non-stationary ISO noise while preserving the boundaries in the estimated HDR images.

关键词： High Dynamic Range Imaging Conditional Random Fields image Denoising HDR Reconstruction SFCRF image denoising hot dry rocks GATA3 gene LAND DISPOSAL RESTRICTIONS Noise images HIGH DYNAMIC RANGE Markov random fields field surveys Noise levels Brackets Cameras

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