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6th International Conference on Social robotics, ICSR 2014

作者： Sorostinean, Mihaela Ferland, François Dang, Thi-Hai-Ha Tapus, Adriana Computer Vision and Robotics Lab Computer Science and System Engineering Department ENSTA-ParisTech Palaiseau France

ISBN: (纸本)9783319119724

Various studies have shown that human visual attention is generally attracted by motion in the field of view. In order to embody this kind of social behavior in a robot, its gaze should focus on key points in its environment, such as objects or humans moving. In this paper, we have developed a social natural attention system and we explore the perception of people while interacting with a robot in three different situations: one where the robot has a totally random gaze behavior, one where its gaze is fixed on the person in the interaction, and one where its gaze behavior adapts to the motion-based environmental context. We conducted an online survey and an on-site experiment with the Meka robot so as to evaluate people’s perception towards these three types of gaze. Our results show that motion-oriented gaze can help to make the robot more engaging and more natural to people. © Springer International Publishing Switzerland 2014.

关键词： Robots

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Impact of personality on the recognition of emotion expressed via human, virtual, and robotic embodiments

Impact of personality on the recognition of emotion expresse...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Pauline Chevalier Jean-Claude Martin Brice Isableu Adriana Tapus Robotics and Computer Vision Lab ENSTA-ParisTech Palaiseau France Jean-Claude Martin is with Cognition Perception Use LIMSI-CNRS Orsay France ClAMS-Motor Control and Perception Univ Paris Sud Orsav France

In this paper, we describe the elaboration and the validation of a body and face database 1 , of 96 videos of 1 to 2 seconds of duration, expressing 4 emotions (i.e., anger, happiness, fear, and sadness) elicited through 4 platforms of increased visual complexity and level of embodiment. The final aim of this database is to develop an individualized training program designed for individuals suffering of autism in order to help them recognize various emotions on different test platforms: two robots, a virtual agent, and a human. Before assessing the recognition capabilities of individuals with ASD, we validated our video database on typically developed individuals (TD). Moreover, we also looked at the relationship between the recognition rate and their personality traits (extroverted (EX) vs. introverted (IN)). We found that the personality of our TD participants did not lead to a different recognition behavior. However, introverted individuals better recognized emotions from less visually complex characters than extroverted individuals.

关键词： Emotion recognition Videos Databases Robots Animation Face Face recognition

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3D Modeling from Wide Baseline Range Scans using Contour Coherence

3D Modeling from Wide Baseline Range Scans using Contour Coh...

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IEEE Conference on computer vision and Pattern Recognition

作者： Ruizhe Wang Jongmoo Choi Gerard Medioni Computer Vision Lab Institute for Robotics and Intelligent Systems University of Southern California

Registering 2 or more range scans is a fundamental problem, with application to 3D modeling. While this problem is well addressed by existing techniques such as ICP when the views overlap significantly at a good initialization, no satisfactory solution exists for wide baseline registration. We propose here a novel approach which leverages contour coherence and allows us to align two wide baseline range scans with limited overlap from a poor initialization. Inspired by ICP, we maximize the contour coherence by building robust corresponding pairs on apparent contours and minimizing their distances in an iterative fashion. We use the contour coherence under a multi-view rigid registration framework, and this enables the reconstruction of accurate and complete 3D models from as few as 4 frames. We further extend it to handle articulations, and this allows us to model articulated objects such as human body. Experimental results on both synthetic and real data demonstrate the effectiveness and robustness of our contour coherence based registration approach to wide baseline range scans, and to 3D modeling.

关键词： Three-dimensional displays Coherence Robustness Cameras Iterative closest point algorithm Shape Vectors

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Motion-oriented attention for a social gaze robot behavior

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8755卷 310-319页

作者： Sorostinean, Mihaela Ferland, François Dang, Thi-Hai-Ha Tapus, Adriana Computer Vision and Robotics Lab Computer Science and System Engineering Department ENSTA-ParisTech Palaiseau France

ISBN: (纸本)9783319119724

Various studies have shown that human visual attention is generally attracted by motion in the field of view. In order to embody this kind of social behavior in a robot, its gaze should focus on key points in its environment, such as objects or humans moving. In this paper, we have developed a social natural attention system and we explore the perception of people while interacting with a robot in three different situations: one where the robot has a totally random gaze behavior, one where its gaze is fixed on the person in the interaction, and one where its gaze behavior adapts to the motion-based environmental context. We conducted an online survey and an on-site experiment with the Meka robot so as to evaluate people’s perception towards these three types of gaze. Our results show that motion-oriented gaze can help to make the robot more engaging and more natural to people. © 2014 Springer International Publishing Switzerland.

关键词： Robots

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KINECT UNBIASED

KINECT UNBIASED

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IEEE International Conference on Image Processing

作者： Manuel Martinez Rainer Stiefelhagen Karlsruhe Institute of Technology Institute for Anthropomatics and Robotics (IAR) Computer Vision for Human-Computer Interaction Lab

ISBN: (纸本)9781479957521

Since its release, Kinect has been the de facto standard for low-cost RGB-D sensors. An infrared laser ray shot through an holographic diffraction grating projects a fixed dot pattern which is captured using an infrared camera. The pseudo-random pattern ensures that a simple block matching algorithm suffices to provide reliable depth estimates, allowing a cost-effective implementation. In this paper, we analyze the software limitations of Kinect's method, which allows us to propose algorithms that provide better precision. First, we analyze the dot pattern: we measure its pincushion distortion and its effect on the dot density, which is smaller towards the edges of the image. Then, we analyze the behavior of Block Matching algorithms, we show how Kinect's Block Matching implementation is;in general;limited by the dot density of the pattern, and a significant spatial bias is introduced as a result. We propose an efficient approach to estimate the disparity of each dot, allowing us to produce a point cloud with better spatial resolution than Block Matching algorithms.

关键词： Kinect RGB-D Pattern Bias

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Facial landmark localization and feature extraction for therapeutic face exercise classification

Communications in Computer and Information Science

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Communications in computer and Information Science 2014年 458卷 179-194页

作者： Lanz, Cornelia Olgay, Birant Sibel Denzler, Joachim Gross, Horst-Michael Neuroinformatics and Cognitive Robotics Lab Ilmenau University of Technology Ilmenau Germany Computer Vision Group Friedrich Schiller University Jena Jena Germany

ISBN: (纸本)9783662449103

In this work, we examine landmark localization and feature extraction approaches for the unexplored topic of therapeutic facial exercise recognition. Our goal is to automatically discriminate nine therapeutic exercises that have been determined in cooperation with speech therapists. We use colour, 2.5D and 3D image data that was recorded using Microsoft’s Kinect. Our features comprise statistical descriptors of the face surface curvature as well as characteristic profiles that are derived from face landmarks. For the nine facial exercises, we yield an average recognition accuracy of about 91% in conjunction with manually labeled landmarks. Additionally, we introduce a combined method for automatic landmark localization and compare the results to landmark positions obtained from Active Appearance Model fitting as well as manual labeling. The combined localization method exhibits increased robustness in comparison to AAMs. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Feature extraction

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2D-3D camera fusion for visual odometry in outdoor environments

2D-3D camera fusion for visual odometry in outdoor environme...

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2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Danda Pani Paudel Cédric Demonceaux Adlane Habed Pascal Vasseur In So Kweon Le2i University of Burgundy France ICube University of Strasbourg France LITIS University of Rouen France Robotics and Computer Vision Lab KAIST Korea

Accurate estimation of camera motion is very important for many robotics applications involving SfM and visual SLAM. Such accuracy is attempted by refining the estimated motion through nonlinear optimization. As many modern robots are equipped with both 2D and 3D cameras, it is both highly desirable and challenging to exploit data acquired from both modalities to achieve a better localization. Existing refinement methods, such as Bundle adjustment and loop closing, may be employed only when precise 2D-to-3D correspondences across frames are available. In this paper, we propose a framework for robot localization that benefits from both 2D and 3D information without requiring such accurate correspondences to be established. This is carried out through a 2D-3D based initial motion estimation followed by a constrained nonlinear optimization for motion refinement. The initial motion estimation finds the best possible 2D-to-3D correspondences and localizes the cameras with respect the 3D scene. The refinement step minimizes the projection errors of 3D points while preserving the existing relationships between images. The problems of occlusion and that of missing scene parts are handled by comparing the image-based reconstruction and 3D sensor measurements. The effect of data inaccuracies is minimized using an M-estimator based technique. Our experiments have demonstrated that the proposed framework allows to obtain a good initial motion estimate and a significant improvement through refinement.

关键词： Cameras Three-dimensional displays Image reconstruction Optimization Lasers Robot sensing systems

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Fast Fog Detection for Camera Based Advanced Driver Assistance Systems

Fast Fog Detection for Camera Based Advanced Driver Assistan...

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IEEE International Conference on Intelligent Transportation Systems

作者： Rita Spinneker Carsten Koch Su-Birm Park Jason Jeongsuk Yoon Hochschule Emden/Leer Automation and Robotics (I2AR) Emden Germany LG Electronics Future IT Lab Computer Vision Team Seoul Republic of Korea

In an increasing number of cars, the driver is supported by Advanced Driver Assistance Systems (ADAS). In particular camera based ADAS are a key component for further improvements in safety and driving comfort. While imaging sensors are performing well under good weather conditions, their efficiency suffers under adverse environmental influences such as heavy rain, fog or snow. To handle such optical threats and to estimate information quality of cameras in order to warn the assistance system of possible critical working conditions, a self-diagnosis mechanism is of great importance for reliable operation of an optical ADAS. In this paper an approach of camera based fog detection as part of a self-diagnosis mechanism for ADAS based on the blurring effect of fog is presented. The encouraging results of our experiments have shown that the presented approach of analysing the power spectrum slope (PSS) of a small image block in close proximity to the vanishing point enables a fast discrimination of street scenes with and without fog.

关键词： Cameras Vehicles Roads Integrated optics Optical imaging Optical sensors Automotive components

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Coping with stress using social robots as emotion-oriented tool: Potential factors discovered from stress game experiment

Coping with stress using social robots as emotion-oriented t...

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5th International Conference on Social robotics, ICSR 2013

作者： Dang, Thi-Hai-Ha Tapus, Adriana Robotics and Computer Vision Lab. ENSTA-Paristech France

ISBN: (纸本)9783319026749

It is known from psychology that humans cope with stress by either changing stress-induced situations (which is called problemoriented coping strategy) or by changing his/her internal perception about the stress-induced situations (which is called emotion-oriented coping strategy). Social robots, as emerging tools that have abilities to socially interact with humans, can be of great use to help people coping with stress. The paper discusses some recent studies about ways of dealing with stress in stressful situations by using social robots. Moreover, we focus on presenting our experimental design and the discovered factors that can allow social robots to assist humans in dealing with stress in an emotion-oriented manner. © Springer International Publishing 2013.

关键词： Machine design

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OBJECT DETECTION USING HIERARCHICAL GRAPH-BASED SEGMENTATION

OBJECT DETECTION USING HIERARCHICAL GRAPH-BASED SEGMENTATION

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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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