Human Sign Recognition for Robot Manipulation

Saldivar-Piñon, Leonardo; Chacón-Murguía, Mario I.; Sandoval-Rodriguez, Rafael; Vega-Pineda, Javier

doi:10.1007/978-3-642-31149-9_11

Cited by 4 publications

(5 citation statements)

References 7 publications

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“…Thus, in order to develop a system as those developed in the reviewed works, such important resources as a 3D avatar or models of the MSL must be created. 3D modeling of the MSL is a significant extension of works related to only modeling hand gestures with limited interpretation as in [13] and [14]. Hence, the information presented in this paper can also contribute to the development of recognition systems for the MSL or other SLs.…”

Section: Modelado 3d Del Lenguaje De Señas Mexicano Para Un Sistema Dmentioning

confidence: 93%

“…As mentioned, an important part of the Speech-to-SL translator is the set of hand configurations which define each MSL unit in the vocabulary set of the system. Some recent works are based on video libraries, and sets of static captures of signs as presented in [13] and [14]. However, this restricts the modeling and its application for recognition purposes with a bigger set of symbols.…”

Section: D Msl Modeling and Avatar Creationmentioning

confidence: 99%

“…However, this restricts the modeling and its application for recognition purposes with a bigger set of symbols. For example, in [13] only five different signs were captured, while in [14] only six were modeled. Especially for SLs, particular attention must be given to fine movements of hands and fingers.…”

Section: D Msl Modeling and Avatar Creationmentioning

confidence: 99%

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3D Modeling of the Mexican Sign Language for a Speech-to-Sign Language System

Caballero‐Morales¹,

Trujillo-Romero²

2013

CyS

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There are many people with communication impairments, deafness being one of the most common of them. Deaf people use Sign Language (SL) to communicate, and translation systems (Speech/Textto-SL) have been developed to assist such communication. However, since SLs are dependent of countries and cultures, there are differences between grammars, vocabularies, and signs, even if these come from places with similar spoken languages. In Mexico, work in this field is very limited, so any development must consider the characteristics of the Mexican-Sign-Language (MSL). In this paper, we present a new approach to creating a Mexican Speech-to-SL system, integrating 3D modeling of the MSL with a multiuser Automatic Speech Recognizer (ASR) with dynamic adaptation. The 3D models (avatar) were developed by means of motion capture of a MSL performer. Kinect was used as a 3D sensor for the motion capture process, and DAZ Studio 4 was used for its animation. The multiuser ASR was developed using the HTK and Matlab as the programming platform for a Graphical User Interface (GUI). Experiments with a vocabulary set of 199 words were performed to validate the system. An accuracy of 96.2% was achieved for the ASR and interpretation into MSL of 70 words and 20 spoken sentences. The 3D avatar presented clearer realizations than those of standard video recordings of a human MSL performer.

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Section: Modelado 3d Del Lenguaje De Señas Mexicano Para Un Sistema Dmentioning

confidence: 93%

Section: D Msl Modeling and Avatar Creationmentioning

confidence: 99%

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3D Modeling of the Mexican Sign Language for a Speech-to-Sign Language System

Caballero‐Morales¹,

Trujillo-Romero²

2013

CyS

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“…Color histograms have been used extensively for user recognition. 32,33 However, they often do not take into account the fact that this color data in a person is naturally structured: A possible segmentation relies on three parts, the head, the upper body (torso and arms, covered by a shirt or another item of clothing), and the lower body (trousers, skirt, etc. ).…”

Section: User Recognitionmentioning

confidence: 99%

A local user mapping architecture for social robots

Ramey

Malfáz

Castillo

et al. 2017

International Journal of Advanced Robotic Systems

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User detection, recognition, and tracking is at the heart of human-robot interaction, and yet, to date, no universal robust method exists for being aware of the people in a robot's surroundings. The present article imports into existing social robotic platforms different techniques, some of them classical, and other novel, for detecting, recognizing, and tracking human users. The outputs from the parallel execution of these algorithms are then merged, creating a modular, expandable, and fast architecture. This results in a local user mapping through fusion of multiple user recognition techniques. The different people detectors comply with a common interface called PeoplePoseList Publisher, while the people recognition algorithms meet an interface called PeoplePoseList Matcher. The fusion of all these different modules is based on the Unscented Kalman Filtering technique. Extensive benchmarks of the subcomponents and of the whole architecture demonstrate the validity and interest of all levels of the architecture. In addition, all the software and data sets generated in this work are freely available.

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“…Mahalanobis distance (MD) is a useful method to calculate the similarity of different samples [ 10 ]. It is used in many fields, including statistics [ 11 ], pattern recognition [ 12 ], and manufacturing control [ 13 ]. In this paper, we focus on the research of belief transferring model.…”

Section: Related Workmentioning

confidence: 99%

Novel Paradigm for Constructing Masses in Dempster-Shafer Evidence Theory for Wireless Sensor Network’s Multisource Data Fusion

Zhang¹,

Liu²,

Zhang³

2014

Sensors

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Dempster-Shafer evidence theory (DSET) is a flexible and popular paradigm for multisource data fusion in wireless sensor networks (WSNs). This paper presents a novel and easy implementing method computing masses from the hundreds of pieces of data collected by a WSN. The transfer model is based on the Mahalanobis distance (MD), which is an effective method to measure the similarity between an object and a sample. Compared to the existing methods, the proposed method concerns the statistical features of the observed data and it is good at transferring multi-dimensional data to belief assignment correctly and effectively. The main processes of the proposed method, which include the calculation of the intersection classes of the power set and the algorithm mapping MDs to masses, are described in detail. Experimental results in transformer fault diagnosis show that the proposed method has a high accuracy in constructing masses from multidimensional data for DSET. Additionally, the results also prove that higher dimensional data brings higher accuracy in transferring data to mass.

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Human Sign Recognition for Robot Manipulation

Cited by 4 publications

References 7 publications

3D Modeling of the Mexican Sign Language for a Speech-to-Sign Language System

3D Modeling of the Mexican Sign Language for a Speech-to-Sign Language System

A local user mapping architecture for social robots

Novel Paradigm for Constructing Masses in Dempster-Shafer Evidence Theory for Wireless Sensor Network’s Multisource Data Fusion

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