2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

1-5 Oct. 2018

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  • [Front cover]

    Publication Year: 2018, Page(s): 1
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  • Program at a Glance

    Publication Year: 2018, Page(s): 4
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  • Welcome message

    Publication Year: 2018, Page(s):11 - 12
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  • 3. Conference Application

    Publication Year: 2018, Page(s):6 - 10
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  • Organizing Committee

    Publication Year: 2018, Page(s):13 - 21
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  • About Madrid

    Publication Year: 2018, Page(s):26 - 32
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  • Sponsors

    Publication Year: 2018, Page(s):33 - 37
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  • Plenary sessions

    Publication Year: 2018, Page(s):38 - 54
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (412 KB)

    Provides an abstract for each of the plenary presentations and may include a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

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  • Forums

    Publication Year: 2018, Page(s):55 - 65
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    Provides an abstract for each of the Forum presentations and may include a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

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  • Workshops

    Publication Year: 2018, Page(s):68 - 90
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    Provides an abstract for each of the workshop presentations and may include a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

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  • IROS 2018 Technical Program

    Publication Year: 2018, Page(s):1 - 12
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  • Content List

    Publication Year: 2018, Page(s):1 - 118
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  • IROS 2018 Author Index

    Publication Year: 2018, Page(s):1 - 41
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  • Index of papers

    Publication Year: 2018, Page(s):1 - 31
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  • Real-time Convolutional Networks for Depth-based Human Pose Estimation

    Publication Year: 2018, Page(s):41 - 47
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (3929 KB) | HTML iconHTML

    We propose to combine recent Convolutional Neural Networks (CNN) models with depth imaging to obtain a reliable and fast multi-person pose estimation algorithm applicable to Human Robot Interaction (HRI) scenarios. Our hypothesis is that depth images contain less structures and are easier to process than RGB images while keeping the required information for human detection and pose inference, thus... View full abstract»

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  • Detection- Tracking for Efficient Person Analysis: The DetTA Pipeline

    Publication Year: 2018, Page(s):48 - 53
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (3476 KB) | HTML iconHTML

    In the past decade many robots were deployed in the wild, and people detection and tracking is an important component of such deployments. On top of that, one often needs to run modules which analyze persons and extract higher level attributes such as age and gender, or dynamic information like gaze and pose. The latter ones are especially necessary for building a reactive, social robot-person int... View full abstract»

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  • 3D Human Pose Estimation on a Configurable Bed from a Pressure Image

    Publication Year: 2018, Page(s):54 - 61
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (1543 KB) | HTML iconHTML Multimedia Media

    Robots have the potential to assist people in bed, such as in healthcare settings, yet bedding materials like sheets and blankets can make observation of the human body difficult for robots. A pressure-sensing mat on a bed can provide pressure images that are relatively insensitive to bedding materials. However, prior work on estimating human pose from pressure images has been restricted to 2D pos... View full abstract»

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  • Estimating Metric Poses of Dynamic Objects Using Monocular Visual-Inertial Fusion

    Publication Year: 2018, Page(s):62 - 68
    Cited by:  Papers (1)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (558 KB) | HTML iconHTML Multimedia Media

    A monocular 3D object tracking system generally has only up-to-scale pose estimation results without any prior knowledge of the tracked object. In this paper, we propose a novel idea to recover the metric scale of an arbitrary dynamic object by optimizing the trajectory of the objects in the world frame, without motion assumptions. By introducing an additional constraint in the time domain, our mo... View full abstract»

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  • Geometric-based Line Segment Tracking for HDR Stereo Sequences

    Publication Year: 2018, Page(s):69 - 74
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (1181 KB) | HTML iconHTML Multimedia Media

    In this work, we propose a purely geometrical approach for the robust matching of line segments for challenging stereo streams with severe illumination changes or High Dynamic Range (HDR) environments. To that purpose, we exploit the univocal nature of the matching problem, i.e. every observation must be corresponded with a single feature or not corresponded at all. We state the problem as a spars... View full abstract»

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  • Adversarial Transfer Networks for Visual Tracking

    Publication Year: 2018, Page(s):75 - 81
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    Visual tracking plays an important role in unmanned systems. In many cases, the system needs to keep track of targets it has never seen before, and the only training sample available is the specified object in the initial frame. In this paper, we propose a deep architecture called adversarial transfer networks (ATNet), which aims to make well use of offline video training data and solve the proble... View full abstract»

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  • Predicting Out-of-View Feature Points for Model-Based Camera Pose Estimation

    Publication Year: 2018, Page(s):82 - 88
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (1176 KB) | HTML iconHTML Multimedia Media

    In this work we present a novel framework that uses deep learning to predict object feature points that are out-of-view in the input image. This system was developed with the application of model-based tracking in mind, particularly in the case of autonomous inspection robots, where only partial views of the object are available. Out-of-view prediction is enabled by applying scaling to the feature... View full abstract»

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  • A modular framework for model-based visual tracking using edge, texture and depth features

    Publication Year: 2018, Page(s):89 - 96
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (4609 KB) | HTML iconHTML Multimedia Media

    We present in this paper a modular real-time model-based visual tracker. It is able to fuse different types of measurement, that is, edge points, textured points, and depth map, provided by one or multiple vision sensors. A confidence index is also proposed for determining if the outputs of the tracker are reliable or not. As expected, experimental results show that the more various measurements a... View full abstract»

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  • FSG: A statistical approach to line detection via fast segments grouping

    Publication Year: 2018, Page(s):97 - 102
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (1271 KB) | HTML iconHTML Multimedia Media

    Line extraction is a preliminary step in various visual robotic tasks performed in low textured scenes such as city and indoor settings. Several efficient line segment detection algorithms such as LSD and EDLines have recently emerged. However, the state of the art segment grouping methods are not robust enough or not amenable for detecting lines in real-time. In this paper we present FSG, a fast ... View full abstract»

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  • Optimized Contrast Enhancements to Improve Robustness of Visual Tracking in a SLAM Relocalisation Context

    Publication Year: 2018, Page(s):103 - 108
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (3547 KB) | HTML iconHTML Multimedia Media

    Robustness of indirect SLAM techniques to light changing conditions remains a central issue in the robotics community. With the change in the illumination of a scene, feature points are either not extracted properly due to low contrasts, or not matched due to large differences in descriptors. In this paper, we propose a multi-layered image representation (MLI) in which each layer holds a contrast ... View full abstract»

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  • Key-frame Selection for Multi-robot Simultaneous Localization and Tracking in Robot Soccer Field

    Publication Year: 2018, Page(s):109 - 116
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (4721 KB) | HTML iconHTML Multimedia Media

    Optical images provide rich features but require extensive computation resources to process for SLAM. When there are limited computation resources on the robots, it becomes a heavy burden to process the images in real-time. This paper presents the design and implementation of key-frame selection algorithm for multiple robots simultaneous localization and tracking on the multi-robot soccer games wh... View full abstract»

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