Integration of a low-cost RGB-D sensor in a social robot for gesture recognition

Ramey, Arnaud; González-Pacheco, Víctor; Salichs, Miguel Á.

doi:10.1145/1957656.1957745

Cited by 58 publications

(33 citation statements)

References 4 publications

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“…Similarly, the appearance of inexpensive RGB-D sensors [33,15], such as Microsoft Kinect released in 2010, triggered a massive wave of interest in 3D visual perception [28]. Access to the color images supplemented with depth maps provided by such sensors changed the the entire field of robotics, starting with their application to map building [26] and SLAM [36,3], through recognition of human posture [7] or hand gestures [27], ending on object grasping [6].…”

Section: Motivation Of the Workmentioning

confidence: 99%

Modreg: A Modular Framework for RGB-D Image Acquisition and 3D Object Model Registration

Kornuta

Stefańczyk

2017

Foundations of Computing and Decision Sciences

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Abstract. RGB-D sensors became a standard in robotic applications requiring object recognition, such as object grasping and manipulation. A typical object recognition system relies on matching of features extracted from RGB-D images retrieved from the robot sensors with the features of the object models. In this paper we present ModReg: a system for registration of 3D models of objects. The system consists of a modular software associated with a multi-camera setup supplemented with an additional pattern projector, used for the registration of high-resolution RGB-D images. The objects are placed on a fiducial board with two dot patterns enabling extraction of masks of the placed objects and estimation of their initial poses. The acquired dense point clouds constituting subsequent object views undergo pairwise registration and at the end are optimized with a graph-based technique derived from SLAM. The combination of all those elements resulted in a system able to generate consistent 3D models of objects.Keywords: ModReg, textured stereo, RGB-D image, point cloud, registration Motivation of the workEmergence of new types of sensors stimulates robotics. Up to the late nineties the most popular sensors used for obstacle avoidance were sonars, whereas the commercialization of laser rangefinders (such as the Hokuyo UTM and SICK LMS series) enabled rapid development of methods for 2D robot pose estimation [21] or techniques for simultaneous localization and map building (SLAM) [38]. Similarly, the appearance of inexpensive RGB-D sensors [33,15], such as Microsoft Kinect released

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Section: Motivation Of the Workmentioning

confidence: 99%

Modreg: A Modular Framework for RGB-D Image Acquisition and 3D Object Model Registration

Kornuta

Stefańczyk

2017

Foundations of Computing and Decision Sciences

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“…Recently, the robot has been expanded with a Microsoft Kinect device [15]. The Kinect sensor is a sensor capable of providing color images and depth maps of the environment simultaneously.…”

Section: Hardwarementioning

confidence: 99%

Maggie: A Social Robot as a Gaming Platform

González-Pacheco

Ramey

Alonso-Martín

et al. 2011

Int J of Soc Robotics

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Edutainment robots are robots designed to participate in people's education and in their entertainment. One of the tasks of edutainment robots is to play with their human partners, but most of them offer a limited pool of games. Moreover, it is difficult to add new games to them. This lack of flexibility could shorten their life cycle. This paper presents a social robot on which several robotic games have been developed. Our robot uses a flexible and modular architecture that allows the creation of new skills by the composition of existing and simpler skills. With this architecture, the development of a new game mainly consists in the composition of the skills that are needed for this specific game. In this paper, we present the robot, its hardware and its software architecture, including its interaction capabilities. We also provide a detailed description of the development of five of the games the robot can play.

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“…While it does not provide a true 3D mesh, an RGB-D image provides more information about the captured object than a traditional 2D color image. RGB-D images have been applied to a variety of tasks such as general object recognition, surface modeling and tracking, modeling indoor environments, discovering objects in scenes, and robotic vision [4,17,18]. Recent papers have also used RGB-D face images for face detection and gender recognition [11,13].…”

Section: Introductionmentioning

confidence: 99%

On RGB-D face recognition using Kinect

Goswami

Bharadwaj

Vatsa

et al. 2013

2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)

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Face recognition algorithms generally use 2D images for feature extraction and matching. In order to achieve better performance, 3D faces captured via specialized acquisition methods have been used to develop improved algorithms. While such 3D images remain difficult to obtain due to several issues such as cost and accessibility, RGB-D images captured by low cost sensors (e.g. Kinect) are comparatively easier to acquire. This research introduces a novel face recognition algorithm for RGB-D images. The proposed algorithm computes a descriptor based on the entropy of RGB-D faces along with the saliency feature obtained from a 2D face. The probe RGB-D descriptor is used as input to a random decision forest classifier to establish the identity. This research also presents a novel RGB-D face database pertaining to 106 individuals. The experimental results indicate that the RGB-D information obtained by Kinect can be used to achieve improved face recognition performance compared to existing 2D and 3D approaches.

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Integration of a low-cost RGB-D sensor in a social robot for gesture recognition

Cited by 58 publications

References 4 publications

Modreg: A Modular Framework for RGB-D Image Acquisition and 3D Object Model Registration

Modreg: A Modular Framework for RGB-D Image Acquisition and 3D Object Model Registration

Maggie: A Social Robot as a Gaming Platform

On RGB-D face recognition using Kinect

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