Real-Time Wrist Localization in Hand Silhouettes

Grzejszczak, Tomasz; Nalepa, Jakub; Kawulok, Michał

doi:10.1007/978-3-319-00969-8_43

Cited by 14 publications

(9 citation statements)

References 8 publications

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“…Therefore, all of the results reported in this paper (for each method from Table 1) have been obtained using ground-truth SPMs. Naturally, if the human skin regions are segmented automatically, then the landmark detection scores are worse than relying on the ground-truth masks, which we demonstrated in our earlier work for the wrist localization case [11].…”

Section: Data Setsmentioning

confidence: 91%

“…Hand landmarks localization is performed in many gesture recognition systems, but usually it is limited to detecting fingertips of extended digits [6,14,17,25,45,54,57], as well as finding the wrist [11,32] and palm region [6,47,51]. This is certainly helpful for estimating a hand pose, when combined with the analysis of some shape features extracted from the hand silhouette or contour.…”

Section: Overview Of Vision-based Gesture Recognitionmentioning

confidence: 99%

“…The aim of this step is to calculate the line that divides the mask of a hand into two parts: hand region and forearm region. The algorithm consists of the following operations [11]:…”

Section: Wrist Line Localizationmentioning

confidence: 99%

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Hand landmarks detection and localization in color images

Grzejszczak

Kawulok

Gałuszka

2015

Multimed Tools Appl

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This paper introduces a new method for detecting and localizing hand landmarks in 2D color images. Location of the hand landmarks is an important source of information for recognizing hand gestures, effectively exploited in a number of recent methods which operate from the depth maps. However, this problem has not yet been satisfactorily solved for 2D color images. Here, we propose to analyze the skin-presence masks, as well as the directional image of a hand using the distance transform and template matching. This makes it possible to detect the landmarks located both at the contour and inside the hand masks. Moreover, we performed an extensive experimental study to compare the proposed method with a number of state-of-the-art algorithms. The obtained quantitative and qualitative results clearly indicate that our approach outperforms other methods, which may help improve the existing gesture recognition systems.

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Section: Data Setsmentioning

confidence: 91%

Section: Overview Of Vision-based Gesture Recognitionmentioning

confidence: 99%

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Hand landmarks detection and localization in color images

Grzejszczak

Kawulok

Gałuszka

2015

Multimed Tools Appl

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“…The problem of hand gesture recognition has been given a considerable research attention due to a wide range of its practical applications, including humancomputer interfaces [1,2], virtual reality [3], telemedicine [4], videoconferencing [5], and more [6,7]. The proposed approaches can be divided into hardwareand vision-based methods.…”

Section: Introductionmentioning

confidence: 99%

Fast and Accurate Hand Shape Classification

Nalepa

Kawulok

2014

Communications in Computer and Information Science

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Abstract. The problem of hand shape classification is challenging since a hand is characterized by a large number of degrees of freedom. Numerous shape descriptors have been proposed and applied over the years to estimate and classify hand poses in reasonable time. In this paper we discuss our parallel framework for real-time hand shape classification applicable in real-time applications. We show how the number of gallery images influences the classification accuracy and execution time of the parallel algorithm. We present the speedup and efficiency analyses that prove the efficacy of the parallel implementation. Noteworthy, different methods can be used at each step of our parallel framework. Here, we combine the shape contexts with the appearance-based techniques to enhance the robustness of the algorithm and to increase the classification score. An extensive experimental study proves the superiority of the proposed approach over existing state-of-the-art methods.

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“…The images fusion task constitute one of the problems which appear when we use image processing systems in such applications as: image recognition [10,11,12] an unmanned aerial vehicle [13,14] used for image acquisition [15,16,17,18], object tracking [19,20,21] or images fusion [22].…”

Section: Introductionmentioning

confidence: 99%

The Fusion of the Visual and Thermal Images on the Basis of Determining the Image Fragments which Contain Essential Details

Kuś

2016

MATEC Web of Conferences

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Abstract. The aim of the following study was to develop a procedure which guarantees the data fusion of thermal and visual images. The first stage of the proposed algorithm consisted of images acquisition which guaranteed that the same parts of images represented the same parts of the observed terrain. The second stage depended on previous information about the searched object features. Two different situations were considered herein. In the case when we had the searched object's feature vector for both representations of a searched object, we could conduct the pattern recognition for each image. It was conducted separately for visual and thermal images. In this way, we obtained the important parts of the images which should be represented in a fused image. The other case examined in the paper, considered the situation in which we did not have the formalised information about the object. In this case, it was necessary to analyse whole images in order to define the potential parts of the images where the object could be found. This analysis should be helpful for an operator to indicate the parts of the images where there are some artefacts which can be the elements of the searched object. Therefore, in this case, the second stage of the algorithm consisted in calculating the local features of the images. These features constituted grey scale gradient computed for the pixels inside the aperture. This study presented the examples of the fused images obtained by means of the developed method.

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Real-Time Wrist Localization in Hand Silhouettes

Cited by 14 publications

References 8 publications

Hand landmarks detection and localization in color images

Hand landmarks detection and localization in color images

Fast and Accurate Hand Shape Classification

The Fusion of the Visual and Thermal Images on the Basis of Determining the Image Fragments which Contain Essential Details

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