Image capture pattern optimization for panoramic photography

Guo, Yuanhao; Zhao, Rongkai; Wu, Song; Wang, Chao

doi:10.1007/s11042-018-5948-y

Cited by 4 publications

(1 citation statement)

References 27 publications

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“…Therefore, when people observe surrounding things, it makes sense to observe different properties of things through different scales. In the actual image processing tasks, everything in the target image has its optimal observation scale [9][10][11]. Therefore, obtaining image spatial information by establishing a micro-time scale has become an effective image feature generation strategy.…”

Section: Introductionmentioning

confidence: 99%

Virtual Reality Image Technology Assists Training Optimization of Motion Micro-Time Scale

Cao

Shang

2020

IEEE Access

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Virtual reality image local features are highly repetitive and are not easily affected by target occlusion, so research on virtual reality image local feature extraction techniques has received increasing attention. For the purpose of global scale selection, this article considers the virtual reality image in the global scope from the theoretical perspectives of the continuity of virtual reality images, the repeatability of virtual reality image features, the scale of scene virtual reality images in the global scope, and the visual saliency. This paper gives a general framework of multi-scale geometric analysis and particle swarm optimization virtual reality image matching algorithm. For the problem of virtual reality image matching, the original particle swarm optimization algorithm is improved. A more reasonable inertia weight change formula, a method for selecting the optimal solution when two objectives are optimized at the same time, and a method for selecting a reasonable input are designed. In this paper, performance evaluation experiments are performed on several feature description algorithms. The experimental results show that the descriptors constructed by these feature description algorithms are significantly more robust than SIFT (Scale Invariant Feature Transform) descriptors. The improved multi-scale geometric analysis and particle swarm optimization are robust due to the introduction of multiple support domains. It has the best discriminative ability, but at the same time, the introduction of multiple support domains leads to the worst real-time algorithm; DGOH (Dual Gradient Orientation Histogram) algorithm is more robust than FRDOH (Fast Representation Based on a Double Orientation Histogram) and SIFT algorithm, and DGOH algorithm has the best real-time performance. INDEX TERMS virtual reality images; particle swarm optimization; multi-scale geometric analysis; inertial weights; feature description.

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Section: Introductionmentioning

confidence: 99%

Virtual Reality Image Technology Assists Training Optimization of Motion Micro-Time Scale

Cao

Shang

2020

IEEE Access

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Visualization techniques to support CCTV operators of smart city services

Pawlowski

Dąbrowski

Balcerek

et al. 2020

Multimed Tools Appl

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In this paper visualization techniques for modern closed circuit television (CCTV) smart city services are discussed with application to prevention of threats. Unconventional approaches to the intelligent visual data processing are proposed in order to support video surveillance operators, thus to make their work less exhaustive and more effective. Although registration of a huge amount of video data requires development of intelligent and automatic signal processing information extraction techniques, improvement of visualization methods for operators is also a very important task, because of the crucial role the human factor plays and should always play in the decision making, e.g. in the operator reactions to various crisis situations, which can never be fully eliminated by artificial intelligence. Four software based mechanisms connected with a standard or with a slightly extended hardware are proposed as options for the CCTV operators. They utilize rather known ideas but are implemented with new extensions to original algorithms, as well as with additional, innovative modifications and solutions (not presented in the literature). With them they become reliable and efficient tools for the CCTV systems. First, generation of cylindrical panoramas is suggested in order to make long-time video content analysis of a defined area easier and faster. Using panoramas it is possible to reduce the time that is required to watch the video by a factor of hundreds or even thousands and perform an efficient compression of the video stream for the long-time storage. Second, the controlled stereovision option is discussed for quicker and more precise extraction of relevant information from the observed scene. Third, the thermo-vision is analyzed for faultless detection of pedestrians at night. Finally, a novel high dynamic range (HDR) technique is proposed, dedicated to the CCTV systems, in contrast to other typical entertainment oriented HDR approaches, for clear visualization of important and meaningful image details, otherwise invisible. We validated usefulness of the proposed techniques with many experiments presented in this paper.

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