The recent years have given rise to a large number of techniques for "looking around corners", i.e., for reconstructing or tracking occluded objects from indirect light reflections off a wall. While the direct view of cameras is routinely calibrated in computer vision applications, the calibration of non-line-of-sight setups has so far relied on manual measurement of the most important dimensions (device positions, wall position and orientation, etc.). In this paper, we propose a method for calibrating time-of-flight-based non-line-of-sight imaging systems that relies on mirrors as known targets. A roughly determined initialization is refined in order to optimize for spatio-temporal consistency. Our system is general enough to be applicable to a variety of sensing scenarios ranging from single sources/detectors via scanning arrangements to large-scale arrays. It is robust towards bad initialization and the achieved accuracy is proportional to the depth resolution of the camera system.
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http://dx.doi.org/10.1364/OE.398647 | DOI Listing |
High-resolution non-line-of-sight (NLOS) imaging under nanosecond time-resolution conditions is challenging in applications. We propose a novel NLOS imaging method consisting of deconvolution modified iterative back projection and virtual modulated range migration for low time-resolution system, obtaining super-resolution (SR) histogram signal and high-resolution NLOS images sequentially. The proposed method is applicable to both confocal and non-confocal configurations.
View Article and Find Full Text PDFNanophotonics
May 2024
National Key Laboratory of Optical Filed Manipulation Science and Technology, Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China.
Non-line-of-sight (NLOS) imaging aims at recovering hidden objects located beyond the traditional line of sight, with potential applications in areas such as security monitoring, search and rescue, and autonomous driving. Conventionally, NLOS imaging requires raster scanning of laser pulses and collecting the reflected photons from a relay wall. High-time-resolution detectors obtain the flight time of photons undergoing multiple scattering for image reconstruction.
View Article and Find Full Text PDFJ Imaging
October 2024
College of Automation & Information Engineering, Xi'an University of Technology, Xi'an 710048, China.
In this paper, a semantic communication-based scheme was proposed to tackle the optimization challenge of transmission efficiency and link stability in indoor visible light communication (VLC) systems utilizing light-emitting diodes for image transmission. The semantic model, established by deep convolutional generative adversarial network (DCGAN) and vector quantization method, can effectively extract the essential characteristics of images. In addition, indoor VLC channel models including line-of-sight (LOS) and non-line-of-sight (NLOS) links are established in a 5*5*3 room, while incorporating noise interference encountered during signal transmission into the training process of the semantic model to enhance its anti-interference capability.
View Article and Find Full Text PDFWith the rapid development of the Internet of Things, location-based services are becoming increasingly important, especially in indoor environments. Visible light positioning (VLP) has garnered widespread attention due to its high accuracy, low cost, and immunity to the radio frequency electromagnetic interference. However, traditional VLP relies on line-of-sight paths, making it impractical in complex and dynamic indoor environments.
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