Image-free real-time detection and tracking of fast moving object using a single-pixel detector

Zhang, Zibang; Ye, Jiaquan; Deng, Qiwen; Zhong, Jingang

doi:10.1364/oe.27.035394

Cited by 58 publications

(13 citation statements)

References 21 publications

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“…The FSI technique can reconstruct high-quality images by acquiring their Fourier spectrum [ 27 ]. The tracking of a single target can be estimated by the FSI technique by measuring 2 Fourier coefficients [ 24 ]. FSI employs a series of Fourier basis patterns to illuminate the target, and each Fourier basis pattern is characterized by its spatial frequency pair

and its initial phase

where

denotes 2-D coordinates in the spatial domain, A is the average intensity of the pattern, and B denotes the contrast.…”

Section: Principle and Methodsmentioning

confidence: 99%

“…The Fourier coefficients of the target image can be acquired using the three-step phase-shifting algorithm [ 24 ]:

…”

Section: Principle and Methodsmentioning

confidence: 99%

“…This method demonstrates that reducing redundancy in data acquisition is an effective approach for the fast tracking method. In [ 24 , 25 ], the method proposed by Zhang et al, based on Fourier single-pixel imaging (FSI), uses six Fourier basis patterns for structured light modulation to measure only two Fourier coefficients to estimate the displacement of a moving object. Recently, a faster method was proposed by Zha and Shi et al; it requires only three geometric moment patterns to illuminate a moving object in one frame [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

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Multi-Target Tracking Using Windowed Fourier Single-Pixel Imaging

Zhang

Shao

et al. 2021

Sensors

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The single-pixel imaging (SPI) technique enables the tracking of moving targets at a high frame rate. However, when extended to the problem of multi-target tracking, there is no effective solution using SPI yet. Thus, a multi-target tracking method using windowed Fourier single-pixel imaging (WFSI) is proposed in this paper. The WFSI technique uses a series of windowed Fourier basis patterns to illuminate the target. This method can estimate the displacements of K independently moving targets by implementing 6K measurements and calculating 2K windowed Fourier coefficients, which is a measurement method with low redundancy. To enhance the capability of the proposed method, we propose a joint estimation approach for multi-target displacement, which solves the problem where different targets in close proximity cannot be distinguished. Using the independent and joint estimation approaches, multi-target tracking can be implemented with WFSI. The accuracy of the proposed multi-target tracking method is verified by numerical simulation to be less than 2 pixels. The tracking effectiveness is analyzed by a video experiment. This method provides, for the first time, an effective idea of multi-target tracking using SPI.

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and its initial phase

where

denotes 2-D coordinates in the spatial domain, A is the average intensity of the pattern, and B denotes the contrast.…”

Section: Principle and Methodsmentioning

confidence: 99%

“…The Fourier coefficients of the target image can be acquired using the three-step phase-shifting algorithm [ 24 ]:

…”

Section: Principle and Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multi-Target Tracking Using Windowed Fourier Single-Pixel Imaging

Zhang

Shao

et al. 2021

Sensors

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show abstract

“…But the method cannot give a position estimate for small targets that lie entirely in one quadrant. The literature [16][17] use structured light to illuminate the target area, exploit the natural optical convolution properties and bucket detection reception to detect and identify the relative offset of the target, but the principle of the imaging is not the same as random speckle-based ghost imaging. It is not convenient to combine with ghost imaging LIDAR.…”

Section: Introductionmentioning

confidence: 99%

Positioning and imaging methods for moving target ghost imaging LIDAR based on correlation intensity weighting

Wang

Chen

et al. 2023

Conference on Infrared, Millimeter, Terahertz Waves and Applications (IMT2022)

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Ghost imaging LIDAR is a new system of gaze imaging radar with high detection sensitivity, super-resolution and better anti-interference performance, but the relative motion between the radar system and the target will make the imaging degenerate. This paper proposes a single-target localization in the field of view by weighting the correlation intensity of rough target images. In a simple background environment, the absolute coordinates of the low-velocity small-size target in the field of view can be obtained. And the reference arm speckles will be compensated in the opposite direction by the translation according to the trajectory obtained by the positioning. An accurate image will be obtained by superimposing many rough images eventually. The proposed correlation intensity weighted positioning, tracking and imaging method has been verified by simulation to be able to locate and image targets in the field of view well.

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“…Toward this, many approaches have been put forward to increase the sampling rate [15][16][17][18][19] or reduce the required number of samplings [20][21][22][23][24][25][26]. Benefits from the fact that tracking usually requires less information than spatially imaging, researchers also propose to acquire the trajectory of the moving object in lower dimension [27] or in Fourier spectrum domain [28], with no image obtained. Considering the nature of GI, information are retrieved by correlation between fluctuations of the bucket signals and the illumination patterns.…”

Section: Introductionmentioning

confidence: 99%

Single-pixel Tracking and Imaging under Weak Illumination

Sun,

Hu,

et al. 2020

Preprint

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Under weak illumination, tracking and imaging moving object turns out to be hard. By spatially collecting the signal, single pixel imaging schemes promise the capability of image reconstruction from low photon flux. However, due to the requirement on large number of samplings, how to clearly image moving objects is an essential problem for such schemes. Here we present a principle of single pixel tracking and imaging method. Velocity vector of the object is obtained from temporal correlation of the bucket signals in a typical computational ghost imaging system. Then the illumination beam is steered accordingly. Taking the velocity into account, both trajectory and clear image of the object are achieved during its evolution. Since tracking is achieved with bucket signals independently, this scheme is valid for capturing moving object as fast as its displacement within the interval of every sampling keeps larger than the resolution of the optical system. Experimentally, our method works well with the average number of detected photons down to 1.88 photons/speckle.

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Image-free real-time detection and tracking of fast moving object using a single-pixel detector

Cited by 58 publications

References 21 publications

Multi-Target Tracking Using Windowed Fourier Single-Pixel Imaging

Multi-Target Tracking Using Windowed Fourier Single-Pixel Imaging

Positioning and imaging methods for moving target ghost imaging LIDAR based on correlation intensity weighting

Single-pixel Tracking and Imaging under Weak Illumination

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