This paper aims to explore an innovative method combining computervision and machine learning to accurately identify and analyze various movements in badminton. This paper first summarizes the application prospect of...
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Untangling of structures like ropes and wires by autonomous robots can be useful in areas such as personal robotics, industries and electrical wiring & repairing by robots. This problem can be tackled by using com...
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ISBN:
(纸本)9781467360999;9781467361002
Untangling of structures like ropes and wires by autonomous robots can be useful in areas such as personal robotics, industries and electrical wiring & repairing by robots. This problem can be tackled by using computervision system in robot. This paper proposes a computervision based method for analyzing visual data acquired from camera for perceiving the overlap of wires, ropes, hoses i.e. detecting tangles. Information obtained after processingimage according to the proposed method comprises of position of tangles in tangled object and which wire passes over which wire. This information can then be used to guide robot to untangle wire/s. Given an image, preprocessing is done to remove noise. Then edges of wire are detected. After that, the image is divided into smaller blocks and each block is checked for wire overlap/s and finding other relevant information. TANGLED-100 dataset was introduced, which consists of images of tangled linear deformable objects. Method discussed in here was tested on the TANGLED-100 dataset. Accuracy achieved during experiments was found to be 74.9%. Robotic simulations were carried out to demonstrate the use of the proposed method in applications of robot. Proposed method is a general method that can be used by robots working in different situations.
In order to realize the functions of tool, workpiece replacement, surface roughness, machining defect and tool wear detection in the process of intelligent manufacturing, a system which can realize in-machine detectio...
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ISBN:
(数字)9781510634107
ISBN:
(纸本)9781510634107
In order to realize the functions of tool, workpiece replacement, surface roughness, machining defect and tool wear detection in the process of intelligent manufacturing, a system which can realize in-machine detection is proposed by combining robot with machine vision detection technology. The overall structure of the system is composed of CNC machine tools, cutting tools, tool shank, camera, lens, computer and so on. The manipulator is calibrated by the method of simultaneous calibration of hand and eye, the clamping device and camera are installed on the manipulator, and the replacement of cutting tool and workpiece can be realized by using industrial imageprocessing algorithm, as well as the in-machine detection of surface roughness, machining defects and tool wear. The experimental results show that the method can meet the requirements of some tests.
image question answering is becoming a very attractive topic in the field of computervision and natural language processing in recent years. In this work, we propose a novel Semantic Bi-Embedded Gated Recurrent Unit ...
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ISBN:
(纸本)9781450371728
image question answering is becoming a very attractive topic in the field of computervision and natural language processing in recent years. In this work, we propose a novel Semantic Bi-Embedded Gated Recurrent Unit (SBE-GRU) method to answer fill-in-the-blank style multiple choice questions for images. Different from the single network, we use the SBE-GRU model to learn the high-level semantic information existing in images. To learn the semantic mapping of an image from the visual level to the language level, we feed the visual-language mappings into a stacked GRU. Moreover, to choose the right answer in the candidate options more simply and effectively, we regard the answer sentence as an answer list while training. In the extensive experiments, the proposed method can get better results compared with the state-of-the-art and CCA methods.
Optical flow is an important computervision technique used for motion estimation, object tracking and activity recognition. In this paper, we study the effectiveness of the optical flow feature in recognizing simple ...
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Deep Learning (DL), a branch of Artificial Intelligence (AI), is extensively used in computervision (CV) technology, particularly in medical image analysis. The DL approaches have achieved notable success in the clas...
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SAR images often receive noise interference in the process of acquisition and transmission, which can greatly reduce the quality of images and cause great difficulties for imageprocessing. The existing complete DCT d...
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SAR images often receive noise interference in the process of acquisition and transmission, which can greatly reduce the quality of images and cause great difficulties for imageprocessing. The existing complete DCT dictionary algorithm is fast in processing speed, but its denoising effect is poor. In this paper, the problem of poor denoising, proposed K-SVD (K-means and singular value decomposition) algorithm is applied to the image noise suppression. Firstly, the sparse dictionary structure is introduced in detail. The dictionary has a compact representation and can effectively train the image signal. Then, the sparse dictionary is trained by K-SVD algorithm according to the sparse representation of the dictionary. The algorithm has more advantages in high dimensional data processing. Experimental results show that the proposed algorithm can remove the speckle noise more effectively than the complete DCT dictionary and retain the edge details better.
Recently, in the era of photography, due to capturing images with limited dynamic range by cameras, High Dynamic Range (HDR) imaging has engrossed people's attention because HDR pictures present more details and b...
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To increase human-computer interaction speed and accuracy, this paper first studies the application of color clustering-based skin color recognition algorithm in finger touch screen. Next, it optimizes rectangular tem...
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ISBN:
(纸本)9781450390200
To increase human-computer interaction speed and accuracy, this paper first studies the application of color clustering-based skin color recognition algorithm in finger touch screen. Next, it optimizes rectangular template-based dynamic threshold algorithm from two aspects: rectangular scanning template size and dynamic threshold selection, thereby proposing a new algorithm for finger visual feature recognition under dynamic conditions. The simulation results indicate that this algorithm is less affected by the environment with higher recognition accuracy, which enables accurate calculation and extraction of center point position of the finger image. Finally, this recognition algorithm is implemented in hardware on FPGA. The test results show that both the imageprocessing speed and algorithm recognition accuracy can meet the requirements of human-computer interaction system.
This article discusses how to apply sensor mixture, modern image handle andcomputervision technology to analyse and to deal with the feature messages of the ground work piece surface flaw, andcomputer how to apply ...
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ISBN:
(纸本)9783037852590
This article discusses how to apply sensor mixture, modern image handle andcomputervision technology to analyse and to deal with the feature messages of the ground work piece surface flaw, andcomputer how to apply the filtered feature messages to identify these flaws. Result shows that this system can find the defect work piece real time from the images for testing.
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