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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Kim, Jungho Choi, Byeongho Kweon, In-So Multimedia IP Research Center KETI Robotics and Computer Vision Lab. KAIST

ISBN: (纸本)9781479903566

Object detection in real images or videos is challenging because the shapes and sizes of objects vary significantly according to their poses, camera viewing direction, and partial occlusion. Previous detection methods employ sliding-window-based schemes that scan windows across an image, requiring many differently shaped windows to capture shape and size variation. In order to solve this problem, we propose an object detection method using hierarchical graph-based segmentation: color-consistent parts are obtained by part-level segmentation and category-consistent regions are found using object-level segmentation. Thus we can avoid scanning a lot of windows across whole images by using part-level segmentation and robustly detect the objects of various shapes and sizes by using object-level segmentation. In addition, we evaluate detection performance using various classifiers with our detection approach.

关键词： Object detection Object classification Graph-based segmentation

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2013 IEEE Conference on computer vision and Pattern Recognition Workshops, CVPRW 2013

作者： Ohn-Bar, Eshed Trivedi, Mohan M. Computer Vision and Robotics Research Lab University of California San Diego CA 92093-0434 United States

ISBN: (纸本)9780769549903

We propose a set of features derived from skeleton tracking of the human body and depth maps for the purpose of action recognition. The descriptors proposed are easy to implement, produce relatively small-sized feature sets, and the multi-class classification scheme is fast and suitable for real-time applications. We intuitively characterize actions using pairwise affinities between view-invariant joint angles features over the performance of an action. Additionally, a new descriptor for spatio-temporal feature extraction from color and depth images is introduced. This descriptor involves an application of a modified histogram of oriented gradients (HOG) algorithm. The application produces a feature set at every frame, and these features are collected into a 2D array which then the same algorithm is applied to again (the approach is termed HOG2). Both feature sets are evaluated in a bag-of-words scheme using a linear SVM, showing state-of-the-art results on public datasets from different domains of human-computer interaction. © 2013 IEEE.

关键词： Human computer interaction

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Intervention AUVs: The Next Challenge

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IFAC Proceedings Volumes 2014年第3期47卷 12146-12159页

作者： Pere Ridao Marc Carreras David Ribas Pedro J. Sanz Gabriel Oliver Computer Vision and Robotics Research Institute Scientific and Technological Park of the University of Girona CIRS Building C/ Pic de Peguera CO 17071 Girona Catalonia - Spain Universitat Jaume I (UJI) Av. Vicent Sos Banyat S/N 12006 Castelln Spain Universitat de les Illes Balears (UIB) Cra. Valldemossa Km 7.5 07122 Palma Spain

While commercially available AUVs are routinely used in survey missions, a new set of applications exists which clearly demand intervention capabilities. The maintenance of: permanent observatories underwater; submerged oil wells; cabled sensor networks; pipes; and the deployment and recovery of benthic stations are but a few of them. These tasks are addressed nowadays using manned submersibles or work-class ROVs, equipped with teleoperated arms under human supervision. Although researchers have recently opened the door to future I-AUVs, a long path is still necessary to pave the way to underwater intervention applications performed in an autonomous way. This paper reviews the evolution timeline in autonomous underwater intervention systems. Milestone projects in the state of the art are reviewed, highlighting their principal contributions to the field. To the best of the authors knowledge only three vehicles have demonstrated some autonomous intervention capabilities so far: ALIVE, SAUVIM and GIRONA 500 I-AUV. Next, GIRONA 500 I-AUV is presented and its software architecture discussed. Recent results in different scenarios are reported: 1) Valve turning and connector plugging/unplugging while docked to a sub-sea panel, 2) Free floating valve turning using learning by demonstration, and 3) Free floating multipurpose multisensory based object recovery. The paper ends discussing the lessons learned so far and presenting the authors view of the future.

关键词： Autonomous Vehicles Robotic Manipulators Marine Systems

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The Power is in Your Hands: 3D Analysis of Hand Gestures in Naturalistic Video

The Power is in Your Hands: 3D Analysis of Hand Gestures in ...

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IEEE Conference on computer vision and Pattern Recognition Workshops

作者： Eshed Ohn-Bar Mohan M. Trivedi Computer Vision and Robotics Research Lab University of California

ISBN: (纸本)9781479909940

We study natural human activity under difficult settings of cluttered background, volatile illumination, and frequent occlusion. To that end, a two-stage method for hand and hand-object interaction detection is developed. First, activity proposals are generated from multiple sub-regions in the scene. Then, these are integrated using a second-stage classifier. We study a set of descriptors for detection and activity recognition in terms of performance and speed. With the overarching goal of reducing 'lab setting bias', a case study is introduced with a publicly available annotated RGB and depth dataset. The dataset was captured using a Kinect under real-world driving settings. The approach is motivated by studying actions-as well as semantic elements in the scene and the driver's interaction with them-which may be used to infer driver inattentiveness. The proposed framework significantly outperforms a state-of-the-art baseline on our dataset for hand detection.

关键词： Hand Dataset three dimensional analysis game player Gestures scaffolding method Human Activities distractability Drivers Videotapes

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vision-based Lane Analysis: Exploration of Issues and Approaches for Embedded Realization

Vision-based Lane Analysis: Exploration of Issues and Approa...

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IEEE Conference on computer vision and Pattern Recognition Workshops

作者： R. K. Satzoda Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California

ISBN: (纸本)9781479909940

Lane feature extraction is one of the key computational steps in lane analysis systems. In this paper, we propose a lane feature extraction method, which enables different configurations of embedded solutions that address both accuracy and embedded systems' constraints. The proposed lane feature extraction process is evaluated in detail using real world lane data, to explore its effectiveness for embedded realization and adaptability to varying contextual information like lane types and environmental conditions.

关键词： Lanes Feature extraction Extraction processes embedding

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Evaluating Open-Universe Face Identification on the Web

Evaluating Open-Universe Face Identification on the Web

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IEEE Conference on computer vision and Pattern Recognition Workshops

作者： Brian C. Becker Enrique G. Ortiz Robotics Institute Carnegie Mellon University Center for Research in Computer Vision University of Central Florida

ISBN: (纸本)9781479909940

Face recognition is becoming a widely used technique to organize and tag photos. Whether searching, viewing, or organizing photos on the web or in personal photo albums, there is a growing demand to index real-world photos by the subjects in them. Even consumer platforms such as Google Picasa, Microsoft Photo Gallery, and social network sites such as Facebook have integrated forms of automated face tagging and recognition;furthermore, a number of libraries and cloud-based APIs that perform face recognition have become available. With such a plethora of choices, comparisons of recent advances become more important to gauge the state of progress in the field. This paper evaluates face identification in the context of not only research algorithms, but also considers consumer photo products, client-side libraries, and cloud-based APIs on a new, large-scale dataset derived from PubFig83 and LFW in a realistic open-universe scenario.

关键词： Facial Recognition webs World Wide Web congenital web Web search engines Facebook Libraries Plethora Social Media Apis integrated forming Social networking web sites websites

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Towards Practical Visual Servoing in robotics

Towards Practical Visual Servoing in Robotics

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Canadian Conference on computer and Robot vision, CRV

作者： Romeo Tatsambon Fomena Camilo Perez Quintero Mona Gridseth Martin Jagersand Computer Vision and Robotics Research Group Department of Computing Science University of Alberta Edmonton AB Canada

ISBN: (纸本)9781467364096

Visual servoing was introduced in robotics nearly 4 decades ago. However until now, there are still only a handful of known examples of application of this technique in addressing real word robotics problems such as disaster response, assistance for elderly or handicapped people, etc. As the world is moving towards the use of robotics to improve quality of life, it is time to assess the challenges involved in applying visual servoing to solve real world problems. This paper presents an overview of these challenges, by asking the question what are the missing components for practical visual servoing? and by providing practical possible solutions for these components. Illustration of these challenges and our current practical solutions are given using our 7-DoFs Barrett WAM Arm.

关键词： Visual servoing Visualization Cameras Target tracking Robot kinematics

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Eshed Ohn-Bar Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

We propose a set of features derived from skeleton tracking of the human body and depth maps for the purpose of action recognition. The descriptors proposed are easy to implement, produce relatively small-sized feature sets, and the multi-class classification scheme is fast and suitable for real-time applications. We intuitively characterize actions using pairwise affinities between view-invariant joint angles features over the performance of an action. Additionally, a new descriptor for spatio-temporal feature extraction from color and depth images is introduced. This descriptor involves an application of a modified histogram of oriented gradients (HOG) algorithm. The application produces a feature set at every frame, and these features are collected into a 2D array which then the same algorithm is applied to again (the approach is termed HOG 2 ). Both feature sets are evaluated in a bag-of-words scheme using a linear SVM, showing state-of-the-art results on public datasets from different domains of human-computer interaction.

关键词： Joints Feature extraction Trajectory Vectors Histograms Accuracy

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An interactive game with a robot: Peoples' perceptions of robot faces and a gesture-based user interface 6

An interactive game with a robot: Peoples' perceptions of ro...

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6th International Conference on Advances in computer-Human Interactions, ACHI 2013

作者： Walters, Michael L. Marcos, Samuel Syrdal, Dag Sverre Dautenhahn, Kerstin Adaptive Systems Research Group University of Hertfordshire Hatfield HertsAL10 9AB United Kingdom CARTIF Foundation Division of Robotics and Computer Vision Parque Tecnologico de Boecillo 205 Boecillo Valladolid47151 Spain

ISBN: (纸本)9781612082509

This paper presents findings from a HRI user-study which investigated participants' perceptions and experiences playing a simple version of the classic game, stone-paper-scissors with a humanoid robot. Participants experienced the robot displaying one of four different robot faces and interacted with the robots using a gesture-based interface. Findings from the study indicated that the effects of the different robot faces were inter-related with participants gender and ratings for overall enjoyment of the game experience. The usability and effectiveness of the gesture-based interface were overall rated positively by participants, though the use of a separate display for the game interface seems to have distracted participants attention from the robot's face. © Copyright IARIA, 2013.

关键词： Human robot interaction

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Single Cluster PHD SLAM: Application to Autonomous Underwater Vehicles using Stereo vision

Single Cluster PHD SLAM: Application to Autonomous Underwate...

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Oceans 2013 - Norway

作者： Sharad Nagappa Narcis Palomeras Chee Sing Lee Nuno Gracias Daniel E. Clark Joaquim Salvi Computer Vision and Robotics Group University of Girona Joint Research Institute in Signal and Image Processing Heriot-Watt University

ISBN: (纸本)9781479900022

This paper considers the application of feature-based simultaneous localisation and mapping (SLAM) using a random finite sets (RFS) framework for an autonomous underwater vehicle. SLAM allows for reduction in localisation error by tracking features which provide a fixed external reference. The SLAM problem is addressed here using a single-cluster probability hypothesis density (PHD) filter. The filter uses a particle approximation for the vehicle position with a conditional Gaussian mixture PHD for the feature map. Map features are selected as unique point features generated from a stereo camera on-board the vehicle. We demonstrate the improvement in localisation applying the algorithm to a dataset obtained in an indoor test tank.

关键词： Autonomous underwater vehicles Stereoviews supersonic low altitude missile underwater vehicles Automatic vehicle location Stereo cameras simultaneous localization and mapping

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