One-shot gesture recognition with attention-based DTW for human-robot collaboration

2019 ◽  
Vol 40 (1) ◽  
pp. 40-47
Author(s):  
Yiqun Kuang ◽  
Hong Cheng ◽  
Yali Zheng ◽  
Fang Cui ◽  
Rui Huang
Keyword(s):  
Gesture Recognition ◽  
Distance Measure ◽  
Local Features ◽  
Feature Descriptor ◽  
Content Type ◽  
High Efficient ◽  
Region Extraction ◽  
Dynamic Time ◽  
Similar Solutions ◽  
Human Robot Collaboration

Purpose This paper aims to present a one-shot gesture recognition approach which can be a high-efficient communication channel in human–robot collaboration systems. Design/methodology/approach This paper applies dynamic time warping (DTW) to align two gesture sequences in temporal domain with a novel frame-wise distance measure which matches local features in spatial domain. Furthermore, a novel and robust bidirectional attention region extraction method is proposed to retain information in both movement and hold phase of a gesture. Findings The proposed approach is capable of providing efficient one-shot gesture recognition without elaborately designed features. The experiments on a social robot (JiaJia) demonstrate that the proposed approach can be used in a human–robot collaboration system flexibly. Originality/value According to previous literature, there are no similar solutions that can achieve an efficient gesture recognition with simple local feature descriptor and combine the advantages of local features with DTW.

scholarly journals Multi-modal gesture recognition with voting-based dynamic time warping

2019 ◽  
Vol 16 (6) ◽  
pp. 172988141989239
Author(s):  
Yiqun Kuang ◽  
Hong Cheng ◽  
Jiasheng Hao ◽  
Ruimeng Xie ◽  
Fang Cui
Keyword(s):  
Gesture Recognition ◽  
Dynamic Time Warping ◽  
Distance Matrix ◽  
Local Features ◽  
Human Robot Interaction ◽  
Time Warping ◽  
Unified Framework ◽  
Depth Sensors ◽  
Critical Issues ◽  
Dynamic Time

Gesture recognition has remained a challenging problem in the fields of human robot interaction. With the development of depth sensors such as Kinect, different modalities become available for gesture recognition while its advantages have not been fully exploited. One of the critical issues for multi-modal gesture recognition is how to fuse features from different modalities. In this article, we present a unified framework for multi-modal gesture recognition based on dynamic time warping. The 3D implicit shape model is applied to characterize the space-time structure of the local features extracted from different modalities. And then, all votes from the local features are incorporated into a common probability space which is then used for building the distance matrix. Meanwhile, an upper-bounding method UB_Pro is proposed to speed up dynamic time warping. The proposed approach is evaluated on the challenging ChaLearn Isolated Gesture Dataset, showing comparable performance in comparison to the state-of-the-art approaches for multi-modal gesture recognition problem.

Towards ubiquitous human gestures recognition using wireless networks

2017 ◽  
Vol 13 (4) ◽  
pp. 408-418 ◽  
Author(s):  
Mustafa S. Aljumaily ◽  
Ghaida A. Al-Suhail
Keyword(s):  
Gesture Recognition ◽  
Channel State Information ◽  
Device Driver ◽  
Recognition System ◽  
Wireless Channel ◽  
New Classification ◽  
Channel State ◽  
State Information ◽  
Content Type ◽  
Human Gestures

Purpose Recently, many researches have been devoted to studying the possibility of using wireless signals of the Wi-Fi networks in human-gesture recognition. They focus on classifying gestures despite who is performing them, and only a few of the previous work make use of the wireless channel state information in identifying humans. This paper aims to recognize different humans and their multiple gestures in an indoor environment. Design/methodology/approach The authors designed a gesture recognition system that consists of channel state information data collection, preprocessing, features extraction and classification to guess the human and the gesture in the vicinity of a Wi-Fi-enabled device with modified Wi-Fi-device driver to collect the channel state information, and process it in real time. Findings The proposed system proved to work well for different humans and different gestures with an accuracy that ranges from 87 per cent for multiple humans and multiple gestures to 98 per cent for individual humans’ gesture recognition. Originality/value This paper used new preprocessing and filtering techniques, proposed new features to be extracted from the data and new classification method that have not been used in this field before.

A novel parameterized digital-mask generation method for projection stereolithography in tissue engineering

2018 ◽  
Vol 24 (6) ◽  
pp. 935-944 ◽  
Author(s):  
Mingke Li ◽  
Wangyu Liu
Keyword(s):  
Computer Aided Design ◽  
Boundary Region ◽  
Additive Manufacture ◽  
3D Scaffold ◽  
Content Type ◽  
Parameterized Design ◽  
High Efficient ◽  
Unit Cells ◽  
Conventional Methods ◽  
Projection Stereolithography

PurposeThe purpose of this paper is to present the novel parameterized digital-mask generation method which is aimed at enhancing bio-scaffold’s fabricating efficiency with digital micro-mirror device (DMD)-based systems.Design/methodology/approachA method to directly generate the digital masks of bio-scaffolds without modeling the entire 3D scaffold models is presented. In most of the conventional methods, it is inefficient to dynamically modify the size of the structural unit cells during design, because it relies more or less on commercial computer aided design (CAD) platforms. The method proposed in this paper can achieve high efficient parameterized design, and it is independent from any CAD platforms. The generated masks in binary bitmap format can be used by the DMD-based to achieve scaffold’s additive manufacture. In conventional methods, the Boolean operation of the external surface and the internal architectures would result in the damage of unit cells in boundary region. These damaged unit cells not only lose its original mechanical property but also cause numbers of gaps and isolated features that would reduce the geometric accuracy of the fabricated scaffolds; the proposed method in this paper provides an approach to tackle this defect.FindingsThe results show that the proposed method can improve the digital masks generation efficiency.Practical implicationsThe proposed method can serve as an effective supplement to the slicing method in additive manufacture. It also provides a way to design and fabricate scaffolds with heterogeneous architectures.Originality/valueThis paper gives supports to fabricate bio-scaffold with DMD-based systems.

The framework of data-driven and multi-criteria decision-making for detecting unbalanced bidding

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huimin Li ◽  
Limin Su ◽  
Jian Zuo ◽  
Xiaowei An ◽  
Guanghua Dong ◽  
...  
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Public Procurement ◽  
Unit Price ◽  
Data Driven ◽  
Relative Distance ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Content Type ◽  
The Government

PurposeUnbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry.Design/methodology/approachThe identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance.FindingsThe proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage.Originality/valueThe data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement.

A novel product recommendation model consolidating price, trust and online reviews

Kybernetes ◽  
2019 ◽  
Vol 48 (6) ◽  
pp. 1355-1372 ◽  
Author(s):  
Ying Huang ◽  
Nu-nu Wang ◽  
Hongyu Zhang ◽  
Jianqiang Wang
Keyword(s):  
Search Engines ◽  
Distance Measure ◽  
Fuzzy Theory ◽  
Online Reviews ◽  
Purchasing Decisions ◽  
Neutrosophic Sets ◽  
Content Type ◽  
Product Recommendation ◽  
Proposed Model

Purpose The purpose of this paper is to propose a model for product recommendation to improve the accuracy of recommendation based on the current search engines used in e-commerce platforms like Tmall.com. Design/methodology/approach First, the proposed model comprehensively considers price, trust and online reviews, which all represent critical factors in consumers’ purchasing decisions. Second, the model introduces the quantization methods for these criteria incorporating fuzzy theory. Third, the model uses a distance measure between two single valued neutrosophic sets based on the prioritized average operator to consolidate the influences of positive, neutral and negative comments. Finally, the model uses multi-criteria decision-making methods to integrate the influences of price, trust and online reviews on purchasing decisions to generate recommendations. Findings To demonstrate the feasibility and efficiency of the proposed model, a case study is conducted based on Tmall.com. The results of case study indicate that the recommendations of our model perform better than those of current search engines of Tmall.com. The proposed model can significantly improve the accuracy of product recommendations based on search engines. Originality/value The product recommendation method can meet the critical challenge from the search engines on e-commerce platforms. In addition, the proposed method could be used in practice to develop a new application for e-commerce platforms.

Linkage analysis using geographical proximity: a test of the efficacy of distance measures

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shumpei Haginoya ◽  
Aiko Hanayama ◽  
Tamae Koike
Keyword(s):  
Environmental Factors ◽  
Euclidean Distance ◽  
Distance Measure ◽  
Distance Measures ◽  
Manhattan Distance ◽  
Geographical Proximity ◽  
Discrimination Accuracy ◽  
Content Type ◽  
Shortest Route ◽  
The Impact

Purpose The purpose of this paper was to compare the accuracy of linking crimes using geographical proximity between three distance measures: Euclidean (distance measured by the length of a straight line between two locations), Manhattan (distance obtained by summing north-south distance and east-west distance) and the shortest route distances. Design/methodology/approach A total of 194 cases committed by 97 serial residential burglars in Aomori Prefecture in Japan between 2004 and 2015 were used in the present study. The Mann–Whitney U test was used to compare linked (two offenses committed by the same offender) and unlinked (two offenses committed by different offenders) pairs for each distance measure. Discrimination accuracy between linked and unlinked crime pairs was evaluated using area under the receiver operating characteristic curve (AUC). Findings The Mann–Whitney U test showed that the distances of the linked pairs were significantly shorter than those of the unlinked pairs for all distance measures. Comparison of the AUCs showed that the shortest route distance achieved significantly higher accuracy compared with the Euclidean distance, whereas there was no significant difference between the Euclidean and the Manhattan distance or between the Manhattan and the shortest route distance. These findings give partial support to the idea that distance measures taking the impact of environmental factors into consideration might be able to identify a crime series more accurately than Euclidean distances. Research limitations/implications Although the results suggested a difference between the Euclidean and the shortest route distance, it was small, and all distance measures resulted in outstanding AUC values, probably because of the ceiling effects. Further investigation that makes the same comparison in a narrower area is needed to avoid this potential inflation of discrimination accuracy. Practical implications The shortest route distance might contribute to improving the accuracy of crime linkage based on geographical proximity. However, further investigation is needed to recommend using the shortest route distance in practice. Given that the targeted area in the present study was relatively large, the findings may contribute especially to improve the accuracy of proactive comparative case analysis for estimating the whole picture of the distribution of serial crimes in the region by selecting more effective distance measure. Social implications Implications to improve the accuracy in linking crimes may contribute to assisting crime investigations and the earlier arrest of offenders. Originality/value The results of the present study provide an initial indication of the efficacy of using distance measures taking environmental factors into account.

scholarly journals Planning to Minimize the Human Muscular Effort during Forceful Human-Robot Collaboration

2022 ◽  
Vol 11 (1) ◽  
pp. 1-27
Author(s):  
Luis F. C. Figueredo ◽  
Rafael De Castro Aguiar ◽  
Lipeng Chen ◽  
Thomas C. Richards ◽  
Samit Chakrabarty ◽  
...  
Keyword(s):  
Muscular Activity ◽  
The Body ◽  
Force Output ◽  
Content Type ◽  
Joint Torques ◽  
Shared Object ◽  
Muscular Load ◽  
Robot Configuration ◽  
Human Robot Collaboration ◽  
Muscular Effort

This work addresses the problem of planning a robot configuration and grasp to position a shared object during forceful human-robot collaboration, such as a puncturing or a cutting task. Particularly, our goal is to find a robot configuration that positions the jointly manipulated object such that the muscular effort of the human, operating on the same object, is minimized while also ensuring the stability of the interaction for the robot. This raises three challenges. First, we predict the human muscular effort given a human-robot combined kinematic configuration and the interaction forces of a task. To do this, we perform task-space to muscle-space mapping for two different musculoskeletal models of the human arm. Second, we predict the human body kinematic configuration given a robot configuration and the resulting object pose in the workspace. To do this, we assume that the human prefers the body configuration that minimizes the muscular effort. And third, we ensure that, under the forces applied by the human, the robot grasp on the object is stable and the robot joint torques are within limits. Addressing these three challenges, we build a planner that, given a forceful task description, can output the robot grasp on an object and the robot configuration to position the shared object in space. We quantitatively analyze the performance of the planner and the validity of our assumptions. We conduct experiments with human subjects to measure their kinematic configurations, muscular activity, and force output during collaborative puncturing and cutting tasks. The results illustrate the effectiveness of our planner in reducing the human muscular load. For instance, for the puncturing task, our planner is able to reduce muscular load by 69.5\% compared to a user-based selection of object poses.

scholarly journals Hybrid Invariant Local Features for Multiple Satellite Image Matching and Registration

2019 ◽  
Vol 9 (2) ◽  
pp. 309-314
Keyword(s):  
Image Matching ◽  
Feature Matching ◽  
Satellite Image ◽  
Remote Sensing Data ◽  
Local Features ◽  
Feature Descriptor ◽  
Matching Method ◽  
Multiple Images ◽  
Feature Sets ◽  
Precise Relationship

Automatic image registration (IR) is very challenging and very important in the field of hyperspectral remote sensing data. Efficient autonomous IR method is needed with high precision, fast, and robust. A key operation of IR is to align the multiple images in single co-ordinate system for extracting and identifying variation between images considered. In this paper, presented a feature descriptor by combining features from both Feature from Accelerated Segment Test (FAST) and Binary Robust Invariant Scalable Key point (BRISK). The proposed hybrid invariant local features (HILF) descriptor extract useful and similar feature sets from reference and source images. The feature matching method allows finding precise relationship or matching among two feature sets. An experimental analysis described the outcome BRISK, FASK and proposed HILF in terms of inliers ratio and repeatability evaluation metrics.

Sign in / Sign up

Export Citation Format

Share Document