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Reconstruction in the Round Using Photometric Normals and Silhouettes.

Reconstruction in the Round Using Photometric Normals and Si...

引用

conference on computer vision and pattern recognition (CVPR)

作者： G. Vogiatzis C. Hernandez R. Cipolla Department of Engineering University of Cambridge Cambridge UK

This paper addresses the problem of obtaining complete, detailed reconstructions of shiny textureless objects. We present an algorithm which uses silhouettes of the object, as well as images obtained under varying illumination conditions. In contrast with previous photometric stereo techniques, ours is not limited to a single viewpoint and produces accurate reconstructions in full 3D. A number of images of the object are obtained from multiple viewpoints, under varying lighting conditions. Starting from the silhouettes, the algorithm recovers camera motion and constructs the object’s visual hull. This is then used to recover the illumination and initialise a multi-view photometric stereo scheme to obtain a closed surface reconstruction. The contributions of the paper are twofold: Firstly we describe a robust technique to estimate light directions and intensities and secondly, we introduce a novel formulation of photometric stereo which combines multiple viewpoints and hence allows closed surface reconstructions. The algorithm has been implemented as a practical model acquisition system. Here, a quantitative evaluation of the algorithm on synthetic data is presented together with a complete reconstruction of a challenging real object.

关键词： Photometry Image reconstruction Stereo vision Surface reconstruction Stereo image processing Shape Lighting Cameras computer vision Reflectivity

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Geometric Hashing with Local Affine Frames

Geometric Hashing with Local Affine Frames

引用

conference on computer vision and pattern recognition (CVPR)

作者： O. Chum J. Matas Center for Machine Perception Czech Technical University Czech Republic CVSSP University of Surrey Guildford UK

We propose a novel representation of local image structure and a matching scheme that are insensitive to a wide range of appearance changes. The representation is a collection of local affine frames that are constructed on outer boundaries of maximally stable extremal regions (MSERS) in an affine-covariant way. Each local affine frame is described by a relative location of other local affine frames in its neighborhood. The image is thus represented by quantities that depend only on the location of the boundaries of MSERs. Inter-image correspondences between local affine frames are formed in constant time by geometric hashing. Direct detection of local afine frames removes the requirement of a point-based hashing to establish reference frames in a combinatorial way, which has in the case of affine transform complexily that is cubic in the number of points. Local affine frames, which are also the quantities represented in the hash table, occupy a 6 0 space and hence data collisions are less likely compared with 2 0 point hashing. Experimentally, the robustness of the method and its insensitiviq to photometric changes is demonstrated on images from different spectral bands of satellite sensor; on images of a transparent object and on images of an object taken during day and night.

关键词： Image recognition Photometry Image retrieval Object recognition computer vision Information retrieval Robustness Satellites Application software Real time systems

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Complete and temporally consistent video outpainting

Complete and temporally consistent video outpainting

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Loï c Dehan Wiebe Van Ranst Patrick Vandewalle Toon Goedemé EAVISE-PSI-ESAT KU Leuven Sint-Katelijne-Waver Belgium

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487405

We describe a novel method for video outpainting. The goal of outpainting is to fill in missing regions at the edges of video frames. Our focus lies on converting portrait (9:16) to landscape (16:9) video. In contrast, most video completion research is focused on inpainting: filling a masked section within the frame based on the remaining, known *** proposed method consists of three main aspects: (1) We form a background estimation using video object segmentation and video inpainting methods, (2) we use optical flow to form temporal consistency, and (3) we propose image shifting to improve individual frame completions. Our method is able to successfully broaden the aspect ratio of a video. On most videos, we achieve realistic results. Only on videos with complex camera motion and foreground objects leaving the frame, the quality is *** contrast to other state-of-the-art methods, our method is able to reconstruct the full frame, including unseen image parts. Moreover, it is temporally consistent. We evaluate our method on the DAVIS and YouTube-VOS datasets. The code is publicly available 1 .

关键词： Measurement computer vision Image edge detection conferences Estimation Object segmentation Filling

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VMCML: Video and Music Matching via Cross-Modality Lifting

VMCML: Video and Music Matching via Cross-Modality Lifting

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Yi-Shan Lee Wei-Cheng Tseng Fu-En Wang Min Sun National Tsing Hua University University of Toronto Vector Institute

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

We propose a content-based system for matching video and background music. The system aims to address the challenges in music recommendation for new users or new music give short-form videos. To this end, we propose a cross-modal framework VMCML (Video and Music Matching via Cross-Modality Lifting) that finds a shared embedding space between video and music representations. To ensure the embedding space can be effectively shared by both representations, we leverage CosFace loss based on margin-based cosine similarity loss. Furthermore, to confirm the music is not the original sound of the video and that more than one video is matched to the same music, we follow the rule and collect videos and music from a well-known multi-media platform. That is because there are limitations of previous datasets. We establish a large-scale dataset called MSV, which provide 390 individual music and the corresponding matched 150,000 videos. We conduct extensive experiments on Youtube-8M and our MSV datasets. Our quantitative and qualitative results demonstrate the effectiveness of our proposed framework and achieve state-of-the-art video and music matching performance.

关键词： computer vision conferences Music Recommender systems pattern matching

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3D Human Scan With A Moving Event Camera

3D Human Scan With A Moving Event Camera

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Kai Kohyama Shintaro Shiba Yoshimitsu Aoki Keio University

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Capturing the 3D human body is one of the important tasks in computer vision with a wide range of applications such as virtual reality and sports analysis. However, conventional frame cameras are limited by their temporal resolution and dynamic range, which imposes constraints in real-world application setups. Event cameras have the advantages of high temporal resolution and high dynamic range (HDR), but the development of event-based methods is necessary to handle data with different characteristics. This paper proposes a novel event-based method for 3D pose estimation and human mesh recovery. Prior work on event-based human mesh recovery require frames (images) as well as event data. The proposed method solely relies on events; it carves 3D voxels by moving the event camera around a stationary body, reconstructs the human pose and mesh by attenuated rays, and fit statistical body models, preserving high-frequency details. The experimental results show that the proposed method outperforms conventional frame-based methods in the estimation accuracy of both pose and body mesh. We also demonstrate results in challenging situations where other frame-based methods suffer from motion blur. This is the first-of-its-kind to demonstrate event-only human mesh recovery, and we hope that it is the first step toward achieving robust and accurate 3D human body scanning from vision sensors.

关键词： computer vision Solid modeling Three-dimensional displays Accuracy Pose estimation Virtual reality vision sensors

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A cross-sensor evaluation of three commercial iris cameras for iris biometrics

A cross-sensor evaluation of three commercial iris cameras f...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Ryan Connaughton Amanda Sgroi Kevin W. Bowyer Patrick Flynn Department of Computer Science and Engineering University of Notre Dame Notre Dame IN USA

As iris biometrics increasingly becomes a large-scale application, the issue of interoperability between iris sensors becomes an important topic of research. This work presents experiments which compare three commercially available iris sensors and investigates the impact of cross-sensor matching on system performance. The sensors are evaluated using three different iris matching algorithms, and conclusions are drawn regarding the interaction between the sensors and the matching algorithm in a cross-sensor scenario.

关键词： Iris recognition Iris Image sensors Sensor systems Prediction algorithms

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DSTCFuse: A Method based on Dual-cycled Cross-awareness of Structure Tensor for Semantic Segmentation via Infrared and Visible Image Fusion

DSTCFuse: A Method based on Dual-cycled Cross-awareness of S...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Xuan Li Rongfu Chen Jie Wang Lei Ma Li Cheng Haiwen Yuan School of Electrical and Information Engineering Wuhan Institute of Technology Hubei Key Laboratory of Optical Information and Pattern Recognition

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Multi-modality information fusion can compensate deficiencies of single modality and provide rich scene information for 2D semantic segmentation. However, the inconsistency in the feature space between different modalities may lead to poor presentation of objects and that would affect subsequent segmented effectiveness. The idea of modal transition can reduce the modal differences and avoid biased processing during the fusion process, but it is hard to perfectly retain the contents of the source images. To address these challenges, a fusion method based on dual-cycled cross-awareness of structure tensor is proposed. Firstly, we propose a dual-cycle modality transition network based on cross-awareness consistency to learn the differences in feature space from different modalities. Secondly, a set of globally structure-tensor preserving modules are designed to enhance the capabilities of the network in capturing complementary features and perceiving global modal consistency. Under the joint constraint of globally structure-tensor awareness loss and cross-awareness loss, our network achieves a robust mapping of feature space from visible to pseudo-infrared images without relying on Ground-Truth. Finally, the pseudo-infrared images that inherit the superior qualities of two modalities are fused with the original infrared images directly, which effectively reduces the complexity of fusion. Extensive comparative experiments show that our method outperforms state-of-the-art methods in qualitative and quantitative evaluation.

关键词： Degradation computer vision Tensors Semantic segmentation conferences Interference pattern recognition

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PUDD: Towards Robust Multi-modal Prototype-based Deepfake Detection

PUDD: Towards Robust Multi-modal Prototype-based Deepfake De...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Alvaro Lopez Pellcier Yi Li Plamen Angelov School of Computing and Communications Lancaster University

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Deepfake techniques generate highly realistic data, making it challenging for humans to discern between actual and artificially generated images. Recent advancements in deep learning-based deepfake detection methods, particularly with diffusion models, have shown remarkable progress. However, there is a growing demand for real-world applications to detect unseen individuals, deepfake techniques, and scenarios. To address this limitation, we propose a Prototype-based Unified Framework for Deepfake Detection (PUDD). PUDD offers a detection system based on similarity, comparing input data against known prototypes for video classification and identifying potential deepfakes or previously unseen classes by analyzing drops in similarity. Our extensive experiments reveal three key findings: (1) PUDD achieves an accuracy of 95.1% on Celeb-DF, outperforming state-of-the-art deepfake detection methods; (2) PUDD leverages image classification as the upstream task during training, demonstrating promising performance in both image classification and deepfake detection tasks during inference; (3) PUDD requires only 2.7 seconds for retraining on new data and emits 10 5 times less carbon compared to the state-of-the-art model, making it significantly more environmentally friendly.

关键词： Training Deepfakes computer vision conferences Computational modeling Prototypes Diffusion models

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Human Carrying Status in Visual Surveillance

Human Carrying Status in Visual Surveillance

引用

conference on computer vision and pattern recognition (CVPR)

作者： Dacheng Tao Xuelong Li S.J. Maybank Xindong Wu School of Computer Science and Information Systems Birkbeck University of London UK Department of Computer Science University of Vermont USA

A person’s gait changes when he or she is carrying an object such as a bag, suitcase or rucksack. As a result, human identification and tracking are made more difficult because the averaged gait image is too simple to represent the carrying status. Therefore, in this paper we first introduce a set of Gabor based human gait appearance models, because Gabor functions are similar to the receptive field profiles in the mammalian cortical simple cells. The very high dimensionality of the feature space makes training difficult. In order to solve this problem we propose a general tensor discriminant analysis (GTDA), which seamlessly incorporates the object (Gabor based human gait appearance model) structure information as a natural constraint. GTDA differs from the previous tensor based discriminant analysis methods in that the training converges. Existing methods fail to converge in the training stage. This makes them unsuitable for practical tasks. Experiments are carried out on the USF baseline data set to recognize a human’s ID from the gait silhouette. The proposed Gabor gait incorporated with GTDA is demonstrated to significantly outperform the existing appearance-based methods.

关键词： Humans Surveillance Tensile stress computer vision Linear discriminant analysis computer science Information analysis Signal processing algorithms pattern recognition Information systems

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A Novel Data Association Algorithm for Object Tracking in Clutter with Application to Tennis Video Analysis

A Novel Data Association Algorithm for Object Tracking in Cl...

引用

conference on computer vision and pattern recognition (CVPR)

作者： Fei Yan A. Kostin W. Christmas J. Kittler Centre for Vision Speech and Signal Processing University of Surrey Guildford Surrey UK

It is well recognised that data association is critically important for object tracking. However, in the presence of successive misdetections, a large number of false candidates and an unknown number of abrupt model switchings that happen unpredictably, the data association problem can be very difficult. We tackle these difficulties by using a layered data association scheme. At the object level, trajectories are "grown" from sets of object candidates that have high probabilities of containing only true positives; by this means the otherwise combinatorial complexity is significantly reduced. Dijkstra’s shortest path algorithm is then used to perform data association at the trajectory level. The algorithm is applied to low-quality tennis video sequences to track a tennis ball. Experiments show that the algorithm is robust to abrupt model switchings, and performs well in heavily cluttered environments.

关键词： Algorithm design and analysis Signal processing algorithms Robustness Iterative algorithms Speech analysis Games Filters Maximum likelihood estimation Polynomials Signal analysis

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