A hand gesture based virtual interface for wheelchair control

Kang, Seong Pal; Rodnay, G.; Tordon, M.; Katupitiya, Jayantha

doi:10.1109/aim.2003.1225441

Cited by 5 publications

(2 citation statements)

References 5 publications

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“…However, as they are put on the bodies of human participants while capturing the data, it often creates inconvenience for the users, especially in their daily life applications. Nowadays, HRI systems are often integrated with the working environments of differentlyabled persons for their routine life activities [8]. In such cases also, harnessing the non-vision-based sensors into the body can become very difficult and cumbersome.…”

Section: Introductionmentioning

confidence: 99%

Visual cue-aided human supervised robot navigation guidance in photometrically challenging environments using adaptive spatial-feature kernel-guided bilateral LPP

Ghosh

Chatterjee

Munshi

2023

Meas. Sci. Technol.

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The objective of an effective human-robot collaborative (HRC) task is the maximization of human-robot competencies while ensuring the user’s convenience. In photometrically challenging and unstructured HRC environments, data obtained from vision sensors often tend to get degraded due to illumination irregularities and spatio-temporal complexities. To extract useful and discriminative features from the data under such situations, locality-sensitive methods like locality preserving projections (LPP) become quite useful as it captures the local geometric structure of the high-dimensional data. In LPP, the local structural information is encoded in the form of weight values between two samples in the higher-dimensional Euclidean space. The weight values are learned in a regular and continuous manner which only depends on the spatial distribution of the data. Moreover, because of its weight dependency solely on the Euclidean distance, improper weight values can occur frequently, as the Euclidean distance is susceptible to noise, outliers, and different types of geometrical transformations. This paper proposes an adaptive weight learning method to be utilized in the weight computation of LPP, which allows it to adaptively select and extract more discriminative features from the higher-dimensional input data while preserving the intrinsic structural information of the data. Additionally, to alleviate the issues with spatial dependency, the concept of bilateral filtering that incorporates the range weights from the feature space along with the similarity weight in the Euclidean space has been utilized here. This paper proposes an augmented version of adaptive spatial-feature kernel-guided bilateral filtering inspired LPP which addresses two of these basic and fundamental issues of the conventional LPP.

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Section: Introductionmentioning

confidence: 99%

Visual cue-aided human supervised robot navigation guidance in photometrically challenging environments using adaptive spatial-feature kernel-guided bilateral LPP

Ghosh

Chatterjee

Munshi

2023

Meas. Sci. Technol.

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“…The main research motivation behind gesture-controlled robot navigation can be traced back to the emerging interest in telepresence in our daily lives [3]. Gesture-controlled systems are getting adapted widely in wheelchairs and accessories for differently-abled persons [4]. Apart from the hands, other approaches like human facial movement, head movement, opening and closing of the mouth, voice, etc, have been used in gesture-controlled wheelchairs [5].…”

Section: Introductionmentioning

confidence: 99%

Weight thresholded regularized robust coding for vision sensing-based hand gesture detection in collaborative robotics

Ghosh,

Paral,

Chatterjee

2023

Phys. Scr.

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Vision sensing-based hand gesture recognition is considered an important contemporary research problem of collaborative robotics in a human-robot coexisting environment. The problem becomes more complex in challenging environments, where a robot needs to correctly recognize a human gesture to perform navigation or some other designated job, even in the presence of poor illumination conditions, occlusion, etc. This work proposes a novel approach of successfully utilizing regularized robust coding (RRC)-based models to solve such hand gesture detection problems in real-life, challenging situations. The RRC model is used for robust regression of a signal or image and is known as an improvement over the classical sparse representation-based classification (SRC) model. In this work, we propose three novel variants of weight thresholding mechanism in conjunction with RRC (namedWTRRC algorithms) which essentially employ more error-tolerant concepts of logistic functions for weight update, when the dictionary is formed by real-world, photometrically irregular hand gesture images. Extensive case studies in real-world environments (i) with poor illumination, and (ii) with both poor illumination and occlusions firmly establish superior performances of the proposed WTRRC variants compared to other state-of-the-art algorithms in such collaborative robotics problems.

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A review on development approaches for 3D gestural embodied human-computer interaction systems

Uba,

Jurewicz

2024

Applied Ergonomics

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A hand gesture based virtual interface for wheelchair control

Cited by 5 publications

References 5 publications

Visual cue-aided human supervised robot navigation guidance in photometrically challenging environments using adaptive spatial-feature kernel-guided bilateral LPP

Visual cue-aided human supervised robot navigation guidance in photometrically challenging environments using adaptive spatial-feature kernel-guided bilateral LPP

Weight thresholded regularized robust coding for vision sensing-based hand gesture detection in collaborative robotics

A review on development approaches for 3D gestural embodied human-computer interaction systems

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