Real-time feature-based video mosaicing at 500 fps

Okumura, Ko; Raut, Sushil; Gu, Qingyi; Aoyama, Tadayoshi; Takaki, Takeshi; Ishii, Idaku

doi:10.1109/iros.2013.6696732

Cited by 21 publications

(8 citation statements)

References 10 publications

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“…The edge feature can represent the contour of a target. Here, the Sobel operator 14 algorithm was selected to collect the edge information. The Sobel edge detection is divided into two steps: …”

Section: Features Extraction For Edge and Cornermentioning

confidence: 99%

“…Santos and Ferreira 13 proposed an FPGA-and fuzzy logic-based position tracking system and proved the possibility of embedding a highlevel logic controller into an FPGA device. Okumura et al 14 proposed a real-time image mosaicing system of high frame rate (up to 500 fps) on FPGA device. Tippetts et al 15 proposed an FPGA-based vision system and applied it on a small unmanned vehicle and illustrated the performance of real-time target tracking.…”

Section: Introductionmentioning

confidence: 99%

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Real-time object tracking system based on field-programmable gate array and convolution neural network

Lyu

Chen

Jiang

et al. 2016

International Journal of Advanced Robotic Systems

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Vision-based object tracking has lots of applications in robotics, like surveillance, navigation, motion capturing, and so on. However, the existing object tracking systems still suffer from the challenging problem of high computation consumption in the image processing algorithms. The problem can prevent current systems from being used in many robotic applications which have limitations of payload and power, for example, micro air vehicles. In these applications, the central processing unit-or graphics processing unit-based computers are not good choices due to the high weight and power consumption. To address the problem, this article proposed a real-time object tracking system based on fieldprogrammable gate array, convolution neural network, and visual servo technology. The time-consuming image processing algorithms, such as distortion correction, color space convertor, and Sobel edge, Harris corner features detector, and convolution neural network were redesigned using the programmable gates in field-programmable gate array. Based on the field-programmable gate array-based image processing, an image-based visual servo controller was designed to drive a two degree of freedom manipulator to track the target in real time. Finally, experiments on the proposed system were performed to illustrate the effectiveness of the real-time object tracking system.

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Section: Features Extraction For Edge and Cornermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Real-time object tracking system based on field-programmable gate array and convolution neural network

Lyu

Chen

Jiang

et al. 2016

International Journal of Advanced Robotic Systems

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“…Mosaicing could be regarded as a special case of scene reconstruction where the images are related by planar homography only [1] . It has been attracted increasing attention in the past few years [2][3][4] . Although existing methods have achieved great performance in real-time applications, obtaining the panorama of the container is not easy because the surveillance camera is installed very close to the container, which causes the video frame only capture a small part of the whole container.…”

Section: Introductionmentioning

confidence: 99%

A fast stitching method for container images using texture and weighted speed

Meng

Zhang²,

Zhang

2019

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019,

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With the rapid development of oceans economy, a huge number of shipping containers are transported all around the world. To reduce the risk of container damages during the transportation, existing solution relies mainly on human beings to observe the container appearance before or after it enters a dock, which is time-consuming and inaccurate. To solve this problem, one intelligent approach is to develop an automatic container damage detection framework based on computer vision techniques. But how to obtain the panorama images for container damage detection is a challenging issue. In this paper, a real-time container panorama producing system is developed based on container surveillance videos, which is implemented by container image stitching with texture features. When there is no reliable offset, the weighted speed for splicing is used. Experimental results indicate that the developed system could achieve approving results in a real-time manner.

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“…Over the last decade, a number of algorithms related to mosaicking [5][6][7][8][9][10][11][12][13][14][15] and super-resolution reconstruction [16][17][18][19][20][21][22][23][24][25][26][27] have been proposed. Super-resolution reconstruction performance has been most influenced by the choice of ML estimation and regularization technique.…”

Section: Introductionmentioning

confidence: 99%