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检索条件"任意字段=2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2014"

共 4555 条记录，以下是41-50 订阅

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An Introduction to the 3rd Workshop on Egocentric (First-person) vision

An Introduction to the 3rd Workshop on Egocentric (First-per...

引用

27th ieee conference on computer vision and pattern recognition (CVPR)

作者： Mann, Steve Kitani, Kris M. Lee, Yong Jae Ryoo, M. S. Fathi, Alireza

ISBN: (纸本)9781479943098

Egocentric vision provides a unique perspective of the visual world that is inherently human-centric. Since egocentric cameras are mounted on the user (typically on the user's head), they are naturally primed to gather visual information from our everyday interactions, and can even act on that information in real-time (e. g. for a vision aid). We believe that this human-centric characteristic of egocentric vision can have a large impact on the way we approach central computer vision tasks such as visual detection, recognition, prediction, and socio-behavioral analysis. By taking advantage of the first-person point-of-view paradigm, there have been recent advances in areas such as personalized video summarization, understanding concepts of social saliency, activity analysis with inside-out cameras (a camera to capture eye gaze and an outward-looking camera), recognizing human interactions and modeling focus of attention. However, in many ways people are only beginning to understand the full potential (and limitations) of the first-person paradigm. In the 3rd workshop on Egocentric (First-Person) vision, we bring together researchers to discuss emerging topics such as: Personalization of visual analysis;Socio-behavioral modeling;Understanding group dynamics and interactions;Egocentric video as big data;First-person vision for robotics;and Egographical User Interfaces (EUIs).

关键词： Sight Cameras group dynamics workshops workshops full potential robotics

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A compact 3D camera suited for mobile and embedded vision applications

A compact 3D camera suited for mobile and embedded vision ap...

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27th ieee conference on computer vision and pattern recognition (CVPR)

作者： Mattoccia, Stefano Marchio, Ilario Casadio, Marco Univ Bologna Sch Engn & Architecture Dept Comp Sci & Engn Bologna Italy

ISBN: (纸本)9781479943098

Recent years have seen the widespread diffusion of 3D sensors, mainly based on active technologies such as structured light and Time-of-Flight, enabling the development of very interesting 3D vision applications. This paper describes a compact 3D camera based on passive stereo vision technology suited for mobile/embedded vision applications. Our 3D camera is very compact, the overall area of the processing unit is smaller than a business card, lightweight, it weights less than 100 g including lenses, has a reduced power consumption, about 2 Watt processing stereo pairs at 30+ fps, and can be easily configured with different baselines and processing units according to specific application requirements. The overall design is mapped on a low cost FPGA, making the hardware design easily portable to other reconfigurable devices, and allows us to obtain in real-time accurate and dense depth maps according to state-of-the-art stereo vision algorithms.

关键词： 3D stereo vision FPGA RGBD depth sensor

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Towards autonomous navigation of miniature UAV

Towards autonomous navigation of miniature UAV

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27th ieee conference on computer vision and pattern recognition (CVPR)

作者： Brockers, Roland Humenberger, Martin Weiss, Stephan Matthies, Larry Jet Prop Lab Pasadena CA 91109 USA Austrian Inst Technol Vienna Austria

ISBN: (纸本)9781479943098

Micro air vehicles such as miniature rotorcrafts require high-precision and fast localization updates for their control, but cannot carry large payloads. Therefore, only small and light-weight sensors and processing units can be deployed on such platforms, favoring vision-based solutions that use light weight cameras and run on small embedded computing platforms. In this paper, we propose a navigation framework to provide a small quadrotor UAV with accurate state estimation for high speed control including 6DoF pose and sensor self-calibration. Our method allows very fast deployment without prior calibration procedures literally rendering the vehicle a throw-and-go platform. Additionally, we demonstrate hazard-avoiding autonomous landing to showcase a high-level navigation capability that relies on the low-level pose estimation results and is executed on the same embedded platform. We explain our hardware-specific implementation on a 12g processing unit and show real-world end-to-end results.

关键词： Micro Air Vehicle autonomous landing autonomous navigation embedded computing vision based state estimation

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Cross-domain fashion image retrieval 31

Cross-domain fashion image retrieval

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ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Gajic, Bojana Baldrich, Ramon Univ Autonoma Barcelona Comp Vis Ctr Edifici O UAB Bellaterra Spain

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Cross domain image retrieval is a challenging task that implies matching images from one domain to their pairs from another domain. In this paper we focus on fashion image retrieval, which involves matching an image of a fashion item taken by users, to the images of the same item taken in controlled condition, usually by professional photographer. When facing this problem, we have different products in train and test time, and we use triplet loss to train the network. We stress the importance of proper training of simple architecture, as well as adapting general models to the specific task.

关键词： Task analysis Streaming media computer vision Image retrieval Biological system modeling conferences Training

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Fast and Robust Perspective Rectification of Document Images on a Smartphone

Fast and Robust Perspective Rectification of Document Images...

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27th ieee conference on computer vision and pattern recognition (CVPR)

作者： Williem Simon, Christian Cho, Sungdae Park, In Kyu Inha Univ Dept Informat & Commun Engn Inchon 402751 South Korea Samsung Elect Co Ltd Div Mobile Commun Suwon 443742 South Korea

ISBN: (纸本)9781479943098

This paper presents a perspective rectification framework for mobile device that is fast and robust to recovering the fronto-parallel view of perspectively distorted document images. The conventional approaches is too heavy to be implemented on a mobile device. In addition, they fails to reject the false case of the perspective rectification. To ameliorate such problems, the proposed framework is designed to pursue a fast and robust algorithm to detect horizontal and vertical vanishing points efficiently and robustly. Then, perspective rectification is performed using both horizontal and vertical vanishing points. In addition, the proposed framework has an adaptive scheme to detect the false case of the perspective rectification and skip the procedure without using the vertical vanishing point. Note that, the proposed framework is designed for consumer application so that bad results are rejected before they are shown for users. We demonstrate the performance of the proposed framework on various challenging examples to confirm that the proposed system is fast and robust in rectifying the perspectively distorted images.

关键词： pattern recognition

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Experiments on an RGB-D Wearable vision System for Egocentric Activity recognition

Experiments on an RGB-D Wearable Vision System for Egocentri...

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27th ieee conference on computer vision and pattern recognition (CVPR)

作者： Moghimi, Mohammad Azagra, Pablo Montesano, Luis Murillo, Ana C. Belongie, Serge Univ Calif San Diego La Jolla CA 92093 USA Univ Zaragoza DIIS I3A Zaragoza Spain Cornell Tech New York NY USA

ISBN: (纸本)9781479943098

This work describes and explores novel steps towards activity recognition from an egocentric point of view. Activity recognition is a broadly studied topic in computer vision, but the unique characteristics of wearable vision systems present new challenges and opportunities. We evaluate a challenging new publicly available dataset that includes trajectories of different users across two indoor environments performing a set of more than 20 different activities. The visual features studied include compact and global image descriptors, including GIST and a novel skin segmentation based histogram signature, and state-of-the art image representations for recognition, including Bag of SIFT words and Convolutional Neural Network (CNN) based features. Our experiments show that simple and compact features provide reasonable accuracy to obtain basic activity information (in our case, manipulation vs. non-manipulation). However, for finer grained categories CNN-based features provide the most promising results. Future steps include integration of depth information with these features and temporal consistency into the pipeline.

关键词： computer vision

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Brain-inspired Classroom Occupancy Monitoring on a Low-Power Mobile Platform

Brain-inspired Classroom Occupancy Monitoring on a Low-Power...

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27th ieee conference on computer vision and pattern recognition (CVPR)

作者： Conti, Francesco Pullini, Antonio Benini, Luca Univ Bologna Dept Elect Elect & Informat Engn I-40126 Bologna Italy Swiss Fed Inst Technol Integrated Syst Lab Zurich Switzerland

ISBN: (纸本)9781479943098

Brain-inspired computer vision (BICV) has evolved rapidly in recent years and it is now competitive with traditional CV approaches. However, most of BICV algorithms have been developed on high power-and-performance platforms (e.g. workstations) or special purpose hardware. We propose two different algorithms for counting people in a classroom, both based on Convolutional Neural Networks (CNNs), a state-of-art deep learning model that is inspired on the structure of the human visual cortex. Furthermore, we provide a standalone parallel C library that implements CNNs and use it to deploy our algorithms on the embedded mobile ARM big. LITTLE-based Odroid-XU platform. Our performance and power measurements show that neuromorphic vision is feasible on off-the-shelf embedded mobile platforms, and we show that it can reach very good energy efficiency for non-time-critical tasks such as people counting.

关键词： brain-inspired computer vision classroom occupancy convolutional neural networks odroid people counting

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Designing a Moral Compass for the Future of computer vision using Speculative Analysis 30

Designing a Moral Compass for the Future of Computer Vision ...

引用

30th ieee/CVF conference on computer vision and pattern recognition workshops (cvprw)

作者： Skirpan, Michael Yeh, Tom Univ Colorado Boulder CO 80309 USA

ISBN: (纸本)9781538607336

In this paper we discuss and analyze possible futures for technologies in the field of computer vision (CV). Using a method we have coined speculative analysis we take a broad look at research trends in the field to categorize risks, analyze which ones are most threatening and likely, and ultimately summarize conclusions for how the field may attempt to stem future harms caused by CV technologies. We develop narrative case studies to provoke dialogue and deeply explore possible risk scenarios we found to be most probable and severe. We arrive at the position that there are serious potentials for CV to cause discriminatory harm and exacerbate cybersecurity issues.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Separating Texture and Illumination for Single-Shot Structured Light Reconstruction

Separating Texture and Illumination for Single-Shot Structur...

引用

ieee conference on computer vision and pattern recognition (CVPR)

作者： Vo, Minh Narasimhan, Srinivasa G. Sheikh, Yaser Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA

ISBN: (纸本)9781479943098

Active illumination based methods have a trade-off between acquisition time and resolution of the estimated 3D shapes. Multi-shot approaches can generate dense reconstructions but require stationary scenes. In contrast, singleshot methods are applicable to dynamic objects but can only estimate sparse reconstructions and are sensitive to surface texture. In this work, we develop a single-shot approach to produce dense reconstructions of highly textured objects. The key to our approach is an image decomposition scheme that can recover the illumination and the texture images from their mixed appearance. Despite the complex appearances of the illuminated textured regions, our method can accurately compute per pixel warps from the illumination pattern and the texture template to the observed image. The texture template is obtained by interleaving the projection sequence with an all-white pattern. Our estimated warping functions are reliable even with infrequent interleaved projection. Thus, we obtain detailed shape reconstruction and dense motion tracking of the textured surfaces. We validate the approach on synthetic and real data containing subtle non-rigid surface deformations.

关键词： Lighting illumination single-shot GRAIN pattern Image decomposition surface texture Reconstructive Surgical Procedures shape reconfiguration texture acquisition time structured light Reconstructions Dense

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On Visible Adversarial Perturbations & Digital Watermarking 31

On Visible Adversarial Perturbations & Digital Watermarking

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ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Hayes, Jamie UCL London England

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Given a machine learning model, adversarial perturbations transform images such that the model's output is classified as an attacker chosen class. Most research in this area has focused on adversarial perturbations that are imperceptible to the human eye. However, recent work has considered attacks that are perceptible but localized to a small region of the image. Under this threat model, we discuss both defenses that remove such adversarial perturbations, and attacks that can bypass these defenses.

关键词： Perturbation methods Watermarking Computational modeling Visualization Task analysis Image restoration computer vision

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