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Byung-Sun Kang and Chang-Hyun Jung
Aqua farms will be the most frequently encountered obstacle when autonomous ships sail along the coastal area of Korea. We used YOLOv5 to create a model that detects aquaculture buoys. The distances between the buoys and the camera were calculated based ...
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Chen Cheng, Dong Liu, Jin-Hui Du and Yong-Zheng Li
The identification and classification of obstacles in navigable and non-navigable regions, as well as the measurement of distances, are crucial topics of investigation in the field of autonomous navigation for unmanned surface vehicles (USVs). Currently,...
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Fei Liu, Jixian Zhang, Jian Wang and Binghao Li
With the extensive development and utilization of urban underground space, coal mines, and other indoor areas, the indoor positioning technology of these areas has become a hot research topic. This paper proposes a robust localization method for indoor m...
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Qifan Xue, Xuanpeng Li, Dong Wang and Weigong Zhang
Sign language recognition (SLR) is a bridge linking the hearing impaired and the general public. Some SLR methods using wearable data gloves are not portable enough to provide daily sign language translation service, while visual SLR is more flexible to ...
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Hirokazu Madokoro, Kazuhito Sato and Nobuhiro Shimoi
This paper presents a vision-based indoor scene recognition method from aerial time-series images obtained using a micro air vehicle (MAV). The proposed method comprises two procedures: a codebook feature description procedure, and a recognition procedur...
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Tong Zhang, Chunjiang Liu, Jiaqi Li, Minghui Pang and Mingang Wang
In view of traditional point-line feature visual inertial simultaneous localization and mapping (SLAM) system, which has weak performance in accuracy so that it cannot be processed in real time under the condition of weak indoor texture and light and sha...
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Guangyu Hou, Haihua Chen, Mingkun Jiang and Runxin Niu
Intelligent agriculture imposes higher requirements on the recognition and localization of fruit and vegetable picking robots. Due to its unique visual information and relatively low hardware cost, machine vision is widely applied in the recognition and ...
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Sina Sajjadi, Mehran Mehrandezh and Farrokh Janabi-Sharifi
In the past two decades, Unmanned Aerial Vehicles (UAVs) have gained attention in applications such as industrial inspection, search and rescue, mapping, and environment monitoring. However, the autonomous navigation capability of UAVs is aggravated in G...
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Prakash Singh
The question that is addressed in this article is whether it matters for collegial leaders to have a binocular vision. Imagine looking through a pair of binoculars as a metaphor for leadership. One lens of the binoculars represents cognitive abilities (I...
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Ka Seng Chou, Teng Lai Wong, Kei Long Wong, Lu Shen, Davide Aguiari, Rita Tse, Su-Kit Tang and Giovanni Pau
This research addresses the challenges of visually impaired individuals? independent travel by avoiding obstacles. The study proposes a distance estimation method for uncontrolled three-dimensional environments to aid navigation towards labeled target ob...
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Yundong Li, Xiaokun Wei and Hanlu Fan
Monocular depth estimation (MDE), as one of the fundamental tasks of computer vision, plays important roles in downstream applications such as virtual reality, 3D reconstruction, and robotic navigation. Convolutional neural networks (CNN)-based methods g...
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Priyank Kalgaonkar and Mohamed El-Sharkawy
Object detection is a computer vision task of detecting instances of objects of a certain class, identifying types of objects, determining its location, and accurately labelling them in an input image or a video. The scope of the work presented within th...
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Hyeseung Park and Seungchul Park
In this paper, we propose a novel unsupervised learning-based model for estimating the depth of monocular images by integrating a simple ResNet-based auto-encoder and some special loss functions. We use only stereo images obtained from binocular cameras ...
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Qianru Teng, Yimin Chen and Chen Huang
We present an occlusion-aware unsupervised neural network for jointly learning three low-level vision tasks from monocular videos: depth, optical flow, and camera motion. The system consists of three different predicting sub-networks simultaneously coupl...
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Qianru Teng, Yimin Chen and Chen Huang
We present an occlusion-aware unsupervised neural network for jointly learning three low-level vision tasks from monocular videos: depth, optical flow, and camera motion. The system consists of three different predicting sub-networks simultaneously coupl...
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