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Detection and accurate localization of circular fiducials under highly challenging conditions

Detection and accurate localization of circular fiducials un...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Calvet, Lilian Gurdjos, Pierre Griwodz, Carsten Gasparini, Simone Simula Research Laboratory Oslo Norway University of Toulouse France

ISBN: (纸本)9781467388511

Using fiducial markers ensures reliable detection and identification of planar features in images. Fiducials are used in a wide range of applications, especially when a reliable visual reference is needed, e.g., to track the camera in cluttered or textureless environments. A marker designed for such applications must be robust to partial occlusions, varying distances and angles of view, and fast camera motions. In this paper, we present a robust, highly accurate fiducial system, whose markers consist of concentric rings, along with its theoretical foundations. Relying on projective properties, it allows to robustly localize the imaged marker and to accurately detect the position of the image of the (common) circle center. We demonstrate that our system can detect and accurately localize these circular fiducials under very challenging conditions and the experimental results reveal that it outperforms other recent fiducial systems.

关键词： computer vision

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Efficiently creating 3D training data for fine hand pose estimation

Efficiently creating 3D training data for fine hand pose est...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Oberweger, Markus Riegler, Gernot Wohlhart, Paul Lepetit, Vincent Institute for Computer Graphics and Vision Graz University of Technology Austria

ISBN: (纸本)9781467388511

While many recent hand pose estimation methods critically rely on a training set of labelled frames, the creation of such a dataset is a challenging task that has been overlooked so far. As a result, existing datasets are limited to a few sequences and individuals, with limited accuracy, and this prevents these methods from delivering their full potential. We propose a semi-automated method for efficiently and accurately labeling each frame of a hand depth video with the corresponding 3D locations of the joints: The user is asked to provide only an estimate of the 2D reprojections of the visible joints in some reference frames, which are automatically selected to minimize the labeling work by efficiently optimizing a sub-modular loss function. We then exploit spatial, temporal, and appearance constraints to retrieve the full 3D poses of the hand over the complete sequence. We show that this data can be used to train a recent state-of-the-art hand pose estimation method, leading to increased accuracy.

关键词： computer vision

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A deeper look at saliency: Feature contrast, semantics, and beyond

A deeper look at saliency: Feature contrast, semantics, and ...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Bruce, Neil D. B. Catton, Christopher Janjic, Sasa University of Manitoba WinnipegMB Canada

ISBN: (纸本)9781467388511

In this paper we consider the problem of visual saliency modeling, including both human gaze prediction and salient object segmentation. The overarching goal of the paper is to identify high level considerations relevant to deriving more sophisticated visual saliency models. A deep learning model based on fully convolutional networks (FCNs) is presented, which shows very favorable performance across a wide variety of benchmarks relative to existing proposals. We also demonstrate that the manner in which training data is selected, and ground truth treated is critical to resulting model behaviour. Recent efforts have explored the relationship between human gaze and salient objects, and we also examine this point further in the context of FCNs. Close examination of the proposed and alternative models serves as a vehicle for identifying problems important to developing more comprehensive models going forward.

关键词： computer vision

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Visually indicated sounds

Visually indicated sounds

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Owens, Andrew Isola, Phillip McDermott, Josh Torralba, Antonio Adelson, Edward H. Freeman, William T. MIT United States U.C. Berkeley United States Google Research United Kingdom

ISBN: (纸本)9781467388511

Objects make distinctive sounds when they are hit or scratched. These sounds reveal aspects of an object's material properties, as well as the actions that produced them. In this paper, we propose the task of predicting what sound an object makes when struck as a way of studying physical interactions within a visual scene. We present an algorithm that synthesizes sound from silent videos of people hitting and scratching objects with a drumstick. This algorithm uses a recurrent neural network to predict sound features from videos and then produces a waveform from these features with an example-based synthesis procedure. We show that the sounds predicted by our model are realistic enough to fool participants in a "real or fake" psychophysical experiment, and that they convey significant information about material properties and physical interactions.

关键词： computer vision

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Learnt quasi-transitive similarity for retrieval from large collections of faces

Learnt quasi-transitive similarity for retrieval from large ...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Arandjelovi, Ognjen University of St. Andrews United Kingdom

ISBN: (纸本)9781467388511

We are interested in identity-based retrieval of face sets from large unlabelled collections acquired in uncontrolled environments. Given a baseline algorithm for measuring the similarity of two face sets, the meta-algorithm introduced in this paper seeks to leverage the structure of the data corpus to make the best use of the available baseline. In particular, we show how partial transitivity of inter-personal similarity can be exploited to improve the retrieval of particularly challenging sets which poorly match the query under the baseline measure. We: (i) describe the use of proxy sets as a means of computing the similarity between two sets, (ii) introduce transitivity meta-features based on the similarity of salient modes of appearance variation between sets, (iii) show how quasi-transitivity can be learnt from such features without any labelling or manual intervention, and (iv) demonstrate the effectiveness of the proposed methodology through experiments on the notoriously challenging YouTube database.

关键词： computer vision

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Generation and comprehension of unambiguous object descriptions

Generation and comprehension of unambiguous object descripti...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Mao, Junhua Huang, Jonathan Toshev, Alexander Camburu, Oana Yuille, Alan Murphy, Kevin Google Inc. United States University of California Los Angeles United States University of Oxford United Kingdom Johns Hopkins University United States

ISBN: (纸本)9781467388511

We propose a method that can generate an unambiguous description (known as a referring expression) of a specific object or region in an image, and which can also comprehend or interpret such an expression to infer which object is being described. We show that our method outperforms previous methods that generate descriptions of objects without taking into account other potentially ambiguous objects in the scene. Our model is inspired by recent successes of deep learning methods for image captioning, but while image captioning is difficult to evaluate, our task allows for easy objective evaluation. We also present a new large-scale dataset for referring expressions, based on MSCOCO. We have released the dataset and a toolbox for visualization and evaluation, see https://***/mjhucla/Google-Refexp-toolbox.

关键词： computer vision

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Fast algorithms for linear and kernel SVM+

Fast algorithms for linear and kernel SVM+

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Li, Wen Dai, Dengxin Tan, Mingkui Xu, Dong Van Gool, Luc Computer Vision Laboratory ETH Zürich Switzerland School of Computer Science University of Adelaide Australia School of Electrical and Information Engineering University of Sydney Australia VISICS ESAT/PSI KU Leuven Belgium

ISBN: (纸本)9781467388511

The SVM+ approach has shown excellent performance in visual recognition tasks for exploiting privileged information in the training data. In this paper, we propose two efficient algorithms for solving the linear and kernel SVM+, respectively. For linear SVM+, we absorb the bias term into the weight vector, and formulate a new optimization problem with simpler constraints in the dual form. Then, we develop an efficient dual coordinate descent algorithm to solve the new optimization problem. For kernel SVM+, we further apply the 2-loss, which leads to a simpler optimization problem in the dual form with only half of dual variables when compared with the dual form of the original SVM+ method. More interestingly, we show that our new dual problem can be efficiently solved by using the SMO algorithm of the one-class SVM problem. Comprehensive experiments on three datasets clearly demonstrate that our proposed algorithms achieve significant speed-up than the state-of-the-art solvers for linear and kernel SVM+.

关键词： computer vision

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Supervised quantization for similarity search

Supervised quantization for similarity search

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Wang, Xiaojuan Zhang, Ting Qi, Guo-Jun Tang, Jinhui Wang, Jingdong Sun Yat-sen University China University of Science and Technology of China China University of Central Florida United States Nanjing University of Science and Technology China Microsoft Research China

ISBN: (纸本)9781467388511

In this paper, we address the problem of searching for semantically similar images from a large database. We present a compact coding approach, supervised quantization. Our approach simultaneously learns feature selection that linearly transforms the database points into a low-dimensional discriminative subspace, and quantizes the data points in the transformed space. The optimization criterion is that the quantized points not only approximate the transformed points accurately, but also are semantically separable: the points belonging to a class lie in a cluster that is not overlapped with other clusters corresponding to other classes, which is formulated as a classification problem. The experiments on several standard datasets show the superiority of our approach over the state-of-the art supervised hashing and unsupervised quantization algorithms.

关键词： pattern recognition

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Learning from the mistakes of others: Matching errors in cross-dataset learning

Learning from the mistakes of others: Matching errors in cro...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Sharmanska, Viktoriia Quadrianto, Novi SMiLe CLiNiC University of Sussex Brighton United Kingdom

ISBN: (纸本)9781467388511

Can we learn about object classes in images by looking at a collection of relevant 3D models? Or if we want to learn about human (inter-)actions in images, can we benefit from videos or abstract illustrations that show these actions? A common aspect of these settings is the availability of additional or privileged data that can be exploited at training time and that will not be available and not of interest at test time. We seek to generalize the learning with privileged information (LUPI) framework, which requires additional information to be defined per image, to the setting where additional information is a data collection about the task of interest. Our framework minimizes the distribution mismatch between errors made in images and in privileged data. The proposed method is tested on four publicly available datasets: Image+ClipArt, Image+3Dobject, and Image+Video. Experimental results reveal that our new LUPI paradigm naturally addresses the cross-dataset learning.

关键词： computer vision

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Globally optimal manhattan frame estimation in real-time

Globally optimal manhattan frame estimation in real-time

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2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Joo, Kyungdon Oh, Tae-Hyun Kim, Junsik Kweon, In So Robotics and Computer Vision Lab. KAIST Korea Republic of

ISBN: (纸本)9781467388511

Given a set of surface normals, we pose a Manhattan Frame (MF) estimation problem as a consensus set maximization that maximizes the number of inliers over the rotation search space. We solve this problem through a branchand-bound framework, which mathematically guarantees a globally optimal solution. However, the computational time of conventional branch-and-bound algorithms are intractable for real-time performance. In this paper, we propose a novel bound computation method within an efficient measurement domain for MF estimation, i.e., the extended Gaussian image (EGI). By relaxing the original problem, we can compute the bounds in real-time, while preserving global optimality. Furthermore, we quantitatively and qualitatively demonstrate the performance of the proposed method for synthetic and real-world data. We also show the versatility of our approach through two applications: extension to multiple MF estimation and video stabilization.

关键词： Problem solving

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