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Article
Publication date: 4 June 2021

Guotao Xie, Jing Zhang, Junfeng Tang, Hongfei Zhao, Ning Sun and Manjiang Hu

To the industrial application of intelligent and connected vehicles (ICVs), the robustness and accuracy of environmental perception are critical in challenging conditions…

357

Abstract

Purpose

To the industrial application of intelligent and connected vehicles (ICVs), the robustness and accuracy of environmental perception are critical in challenging conditions. However, the accuracy of perception is closely related to the performance of sensors configured on the vehicle. To enhance sensors’ performance further to improve the accuracy of environmental perception, this paper aims to introduce an obstacle detection method based on the depth fusion of lidar and radar in challenging conditions, which could reduce the false rate resulting from sensors’ misdetection.

Design/methodology/approach

Firstly, a multi-layer self-calibration method is proposed based on the spatial and temporal relationships. Next, a depth fusion model is proposed to improve the performance of obstacle detection in challenging conditions. Finally, the study tests are carried out in challenging conditions, including straight unstructured road, unstructured road with rough surface and unstructured road with heavy dust or mist.

Findings

The experimental tests in challenging conditions demonstrate that the depth fusion model, comparing with the use of a single sensor, can filter out the false alarm of radar and point clouds of dust or mist received by lidar. So, the accuracy of objects detection is also improved under challenging conditions.

Originality/value

A multi-layer self-calibration method is conducive to improve the accuracy of the calibration and reduce the workload of manual calibration. Next, a depth fusion model based on lidar and radar can effectively get high precision by way of filtering out the false alarm of radar and point clouds of dust or mist received by lidar, which could improve ICVs’ performance in challenging conditions.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 22 July 2021

Zirui Guo, Huimin Lu, Qinghua Yu, Ruibin Guo, Junhao Xiao and Hongshan Yu

This paper aims to design a novel feature descriptor to improve the performance of feature matching in challenge scenes, such as low texture and wide-baseline scenes. Common…

Abstract

Purpose

This paper aims to design a novel feature descriptor to improve the performance of feature matching in challenge scenes, such as low texture and wide-baseline scenes. Common descriptors are not suitable for low texture scenes and other challenging scenes mainly owing to encoding only one kind of features. The proposed feature descriptor considers multiple features and their locations, which is more expressive.

Design/methodology/approach

A graph neural network–based descriptors enhancement algorithm for feature matching is proposed. In this paper, point and line features are the primary concerns. In the graph, commonly used descriptors for points and lines constitute the nodes and the edges are determined by the geometric relationship between points and lines. After the graph convolution designed for incomplete join graph, enhanced descriptors are obtained.

Findings

Experiments are carried out in indoor, outdoor and low texture scenes. The experiments investigate the real-time performance, rotation invariance, scale invariance, viewpoint invariance and noise sensitivity of the descriptors in three types of scenes. The results show that the enhanced descriptors are robust to scene changes and can be used in wide-baseline matching.

Originality/value

A graph structure is designed to represent multiple features in an image. In the process of building graph structure, the geometric relation between multiple features is used to establish the edges. Furthermore, a novel hybrid descriptor for points and lines is obtained using graph convolutional neural network. This enhanced descriptor has the advantages of both point features and line features in feature matching.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 18 September 2023

Yong Qin and Haidong Yu

This paper aims to provide a better understanding of the challenges and potential solutions in Visual Simultaneous Localization and Mapping (SLAM), laying the foundation for its…

Abstract

Purpose

This paper aims to provide a better understanding of the challenges and potential solutions in Visual Simultaneous Localization and Mapping (SLAM), laying the foundation for its applications in autonomous navigation, intelligent driving and other related domains.

Design/methodology/approach

In analyzing the latest research, the review presents representative achievements, including methods to enhance efficiency, robustness and accuracy. Additionally, the review provides insights into the future development direction of Visual SLAM, emphasizing the importance of improving system robustness when dealing with dynamic environments. The research methodology of this review involves a literature review and data set analysis, enabling a comprehensive understanding of the current status and prospects in the field of Visual SLAM.

Findings

This review aims to comprehensively evaluate the latest advances and challenges in the field of Visual SLAM. By collecting and analyzing relevant research papers and classic data sets, it reveals the current issues faced by Visual SLAM in complex environments and proposes potential solutions. The review begins by introducing the fundamental principles and application areas of Visual SLAM, followed by an in-depth discussion of the challenges encountered when dealing with dynamic objects and complex environments. To enhance the performance of SLAM algorithms, researchers have made progress by integrating different sensor modalities, improving feature extraction and incorporating deep learning techniques, driving advancements in the field.

Originality/value

To the best of the authors’ knowledge, the originality of this review lies in its in-depth analysis of current research hotspots and predictions for future development, providing valuable references for researchers in this field.

Details

Industrial Robot: the international journal of robotics research and application, vol. 50 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 11 March 2024

Jianjun Yao and Yingzhao Li

Weak repeatability is observed in handcrafted keypoints, leading to tracking failures in visual simultaneous localization and mapping (SLAM) systems under challenging scenarios…

Abstract

Purpose

Weak repeatability is observed in handcrafted keypoints, leading to tracking failures in visual simultaneous localization and mapping (SLAM) systems under challenging scenarios such as illumination change, rapid rotation and large angle of view variation. In contrast, learning-based keypoints exhibit higher repetition but entail considerable computational costs. This paper proposes an innovative algorithm for keypoint extraction, aiming to strike an equilibrium between precision and efficiency. This paper aims to attain accurate, robust and versatile visual localization in scenes of formidable complexity.

Design/methodology/approach

SiLK-SLAM initially refines the cutting-edge learning-based extractor, SiLK, and introduces an innovative postprocessing algorithm for keypoint homogenization and operational efficiency. Furthermore, SiLK-SLAM devises a reliable relocalization strategy called PCPnP, leveraging progressive and consistent sampling, thereby bolstering its robustness.

Findings

Empirical evaluations conducted on TUM, KITTI and EuRoC data sets substantiate SiLK-SLAM’s superior localization accuracy compared to ORB-SLAM3 and other methods. Compared to ORB-SLAM3, SiLK-SLAM demonstrates an enhancement in localization accuracy even by 70.99%, 87.20% and 85.27% across the three data sets. The relocalization experiments demonstrate SiLK-SLAM’s capability in producing precise and repeatable keypoints, showcasing its robustness in challenging environments.

Originality/value

The SiLK-SLAM achieves exceedingly elevated localization accuracy and resilience in formidable scenarios, holding paramount importance in enhancing the autonomy of robots navigating intricate environments. Code is available at https://github.com/Pepper-FlavoredChewingGum/SiLK-SLAM.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 26 August 2014

Lounis Chermak, Nabil Aouf and Mark Richardson

In visual-based applications, lighting conditions have a considerable impact on quality of the acquired images. Extremely low or high illuminated environments are a real issue for…

Abstract

Purpose

In visual-based applications, lighting conditions have a considerable impact on quality of the acquired images. Extremely low or high illuminated environments are a real issue for a majority of cameras due to limitations in their dynamic range. Indeed, over or under exposure might result in loss of essential information because of pixel saturation or noise. This can be critical in computer vision applications. High dynamic range (HDR) imaging technology is known to improve image rendering in such conditions. The purpose of this paper is to investigate the level of performance that can be achieved for feature detection and tracking operations in images acquired with a HDR image sensor.

Design/methodology/approach

In this study, four different feature detection techniques are selected and tracking algorithm is based on the pyramidal implementation of Kanade-Lucas-Tomasi (KLT) feature tracker. Tracking algorithm is run over image sequences acquired with a HDR image sensor and with a high resolution 5 Megapixel image sensor to comparatively assess them.

Findings

The authors demonstrate that tracking performance is greatly improved on image sequences acquired with HDR sensor. Number and percentage of finally tracked features are several times higher than what can be achieved with a 5 Megapixel image sensor.

Originality/value

The specific interest of this work focuses on the evaluation of tracking persistence of a set of initial detected features over image sequences taken in different scenes. This includes extreme illumination indoor and outdoor environments subject to direct sunlight exposure, backlighting, as well as dim light and dark scenarios.

Details

Kybernetes, vol. 43 no. 8
Type: Research Article
ISSN: 0368-492X

Keywords

Abstract

Details

Challenges of the Muslim World
Type: Book
ISBN: 978-0-444-53243-5

Book part
Publication date: 24 November 2022

Jasmine Yu-Hsing Chen

This chapter examines how the breakthrough of Zhang Ziyi's depiction of a female kung fu master in The Grandmaster (2013) transforms the figure of the heroine in Chinese action…

Abstract

This chapter examines how the breakthrough of Zhang Ziyi's depiction of a female kung fu master in The Grandmaster (2013) transforms the figure of the heroine in Chinese action films. Zhang is well known for her acting in action films conducted by renowned directors, such as Ang Lee, Zhang Yimou and Wong Kar-wai. After winning 12 different Best Actress awards for her portrayal of Gong Ruomei in The Grandmaster, Zhang announced that she would no longer perform in any action films to show her highest respect for the superlative character Gong. Tracing Zhang's transformational portrait of a heroine in The Grandmaster alongside her other action roles, this analysis demonstrates how her performance projects the directors' distinctive gender viewpoints. I argue that Zhang's characterisation of Gong remodels heroine-hood in Chinese action films. Inheriting the typical plot of a daughter's use of martial arts for revenge for her father's death, Gong breaks from conventional Chinese action films that highlight romantic love during a woman's adventure and the decisive final battle scene. Beyond the propensity for sensory stimulation, Gong's characterisation enables Zhang to determine that women can really act in action films – demonstrating their inner power and ability to create multi-layered characters – not merely relying upon physical action. This chapter offers a relational perspective of how women transform the action film genre not merely as gender spectacles but as embodied figures that represent emerging female subjectivity.

Details

Gender and Action Films
Type: Book
ISBN: 978-1-80117-514-2

Keywords

Article
Publication date: 22 July 2009

Lai Chiu

While the concept of cultural competence has emerged as a major contribution to improving migrants' and minority ethnic (MME) health, what constitutes culturally competent health…

Abstract

While the concept of cultural competence has emerged as a major contribution to improving migrants' and minority ethnic (MME) health, what constitutes culturally competent health promotion is less well understood. This paper explores the tension between the concept of cultural competence and community empowerment through an analysis of the author's recent experience of a participatory video project in which four ethnic/language groups were involved in the production of a breast‐screening video. It illustrates the engagement of migrants and minority ethnic communities in different stages of the video production process, and critically reflects on how this experience could be understood. It concludes that culturally competent health promotion requires us to go beyond language and cultural sensitivity to engage critically with communities to participate in health promotion activities. Participatory video has the potential not only to promote health messages in the communities, but also to strengthen capacity and cultural identities.

Details

International Journal of Migration, Health and Social Care, vol. 5 no. 1
Type: Research Article
ISSN: 1747-9894

Keywords

Article
Publication date: 18 January 2024

Huazhou He, Pinghua Xu, Jing Jia, Xiaowan Sun and Jingwen Cao

Fashion merchandising hold a paramount position within the realm of retail marketing. Currently, the purpose of this article is that the assessment of display effectiveness…

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Abstract

Purpose

Fashion merchandising hold a paramount position within the realm of retail marketing. Currently, the purpose of this article is that the assessment of display effectiveness predominantly relies on the subjective judgment of merchandisers due to the absence of an effective evaluation method. Although eye-tracking devices have found extensive used in tracking the gaze trajectory of subject, they exhibit limitations in terms of stability when applied to the evaluation of various scenes. This underscores the need for a dependable, user-friendly and objective assessment method.

Design/methodology/approach

To develop a cost-effective and convenient evaluation method, the authors introduced an image processing framework for the assessment of variations in the impact of store furnishings. An optimized visual saliency methodology that leverages a multiscale pyramid model, incorporating color, brightness and orientation features, to construct a visual saliency heatmap. Additionally, the authors have established two pivotal evaluation indices aimed at quantifying attention coverage and dispersion. Specifically, bottom features are extract from 9 distinct scale images which are down sampled from merchandising photographs. Subsequently, these extracted features are amalgamated to form a heatmap, serving as the focal point of the evaluation process. The authors have proposed evaluation indices dedicated to measuring visual focus and dispersion, facilitating a precise quantification of attention distribution within the observed scenes.

Findings

In comparison to conventional saliency algorithm, the optimization method yields more intuitive feedback regarding scene contrast. Moreover, the optimized approach results in a more concentrated focus within the central region of the visual field, a pattern in alignment with physiological research findings. The results affirm that the two defined indicators prove highly effective in discerning variations in visual attention across diverse brand store displays.

Originality/value

The study introduces an intelligent and cost-effective objective evaluate method founded upon visual saliency. This pioneering approach not only effectively discerns the efficacy of merchandising efforts but also holds the potential for extension to the assessment of fashion advertisements, home design and website aesthetics.

Details

International Journal of Clothing Science and Technology, vol. 36 no. 1
Type: Research Article
ISSN: 0955-6222

Keywords

Article
Publication date: 15 May 2023

Lin Wang, Huaxia Gao and Yang Zhao

Contextual cues have become a hot research topic in the field of mobile consumer behavior, owing to the continuous rise of digital marketing. However, the complex online shopping…

Abstract

Purpose

Contextual cues have become a hot research topic in the field of mobile consumer behavior, owing to the continuous rise of digital marketing. However, the complex online shopping scene makes it challenging to directly identify the association between the characteristics of contextual cues and consumer behavior. Presently, few studies have only systematically extracted and refined the types and characteristics of contextual cues. The purpose of this study is to explore the types and mechanisms of contextual cues in online shopping scenarios.

Design/methodology/approach

This study uses the word2vec algorithm, grounded theory and co-occurrence cluster method, along with online shopping word-of-mouth (WOM) text and consumer behavior theory, in order to explore different types of contextual cues and its efficiency from 5,619 comment corpus.

Findings

This study puts forward the following conclusions. (1) From the perspective of online shopping, contextual cues comprise aesthetic perception cues, value perception cues, trust-dependent cues, time perception cues, memory attention cues, spatial perception cues, attribute cues and relationship cues. (2) Based on the online shopping scenarios, contextual cues and their interaction effects exert an effect on consumer satisfaction, recommendation, purchase and return behavior.

Originality/value

The study conclusions are helpful to further reveal the deep association between contextual cues and consumer behavior in the process of online shopping, thus providing practical and theoretical enlightenment for enterprises to not only effectively reshape the scene but also promote the consumers' active purchase behavior.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 35 no. 11
Type: Research Article
ISSN: 1355-5855

Keywords

1 – 10 of over 17000