Interference Model of Two Time-Of-Flight Cameras

Wermke, Felix; Meffert, Beate

doi:10.1109/sensors43011.2019.8956892

Cited by 3 publications

(4 citation statements)

References 6 publications

(7 reference statements)

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“…V int (x, y, z) = V matrix − V intorigin (18) where V int (x, y, z) is a vector associated with a pixel (x, y), V intorigin (x, y, z) is the physical location of the interfering secondary ToF sensor within the scene, and V matrix (x, y, z) is the virtual physical location of each pixel of the probability map within the scene.…”

Section: Ray Tracingmentioning

confidence: 99%

“…In such a situation, there is an increasing likelihood of these sensors causing interference to each other during regular operation in many practical settings, such as multiple cameras imaging the same object or subject. There are only a limited number of previous works that quantify the behavior of multicamera interference in 3D images (e.g., depth maps) that is captured by a time-of-flight (ToF) sensor using infrared (IR) light [14][15][16][17][18][19]. Existing works describe the behavior of multicamera interference using a simple mathematical model based on a summation of modulated light signals that corresponds with the IR light that is emitted from each ToF sensor [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic Modeling of Multicamera Interference for Time-of-Flight Sensors

Rodriguez,

Zhang,

Rajan

2023

Sensors

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The behavior of multicamera interference in 3D images (e.g., depth maps), which is based on infrared (IR) light, is not well understood. In 3D images, when multicamera interference is present, there is an increase in the amount of zero-value pixels, resulting in a loss of depth information. In this work, we demonstrate a framework for synthetically generating direct and indirect multicamera interference using a combination of a probabilistic model and ray tracing. Our mathematical model predicts the locations and probabilities of zero-value pixels in depth maps that contain multicamera interference. Our model accurately predicts where depth information may be lost in a depth map when multicamera interference is present. We compare the proposed synthetic 3D interference images with controlled 3D interference images captured in our laboratory. The proposed framework achieves an average root mean square error (RMSE) of 0.0625, an average peak signal-to-noise ratio (PSNR) of 24.1277 dB, and an average structural similarity index measure (SSIM) of 0.9007 for predicting direct multicamera interference, and an average RMSE of 0.0312, an average PSNR of 26.2280 dB, and an average SSIM of 0.9064 for predicting indirect multicamera interference. The proposed framework can be used to develop and test interference mitigation techniques that will be crucial for the successful proliferation of these devices.

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Section: Ray Tracingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Probabilistic Modeling of Multicamera Interference for Time-of-Flight Sensors

Rodriguez,

Zhang,

Rajan

2023

Sensors

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“…[1], [2]. Multiple ToF cameras, using the same modulation frequency, may interfere with each other and cause errors in the distance measurements [3]- [8]. To avoid interference errors Büttgen and Seitz proposed channel access methods adopted from communication systems: space-division multiple access (SDMA), wavelength-division multiple access (WDMA), time-division multiple access (TDMA), frequency-division multiple access (FDMA) and code-division multiple access (CDMA) [9], [10].…”

Section: Introductionmentioning

confidence: 99%

Synchronization of Multiple Time-of-Flight Cameras Using Photodiodes

2020

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Time-of-flight (ToF) cameras are an evolving technology, finding applications in a wide range of fields, including machine vision, automotive applications, face or hand recognition, and human-robot collaboration. A setup consisting of multiple ToF cameras can provide a 3-D model of the recorded scene with a larger field of view and avoid occlusion. The operating principle of ToF cameras' requires the emission of light to measure its round-trip time to the objects in the field of view and the reflection back to the camera. If multiple ToF cameras operate simultaneously, their light waves may interfere, resulting in erroneous depth measurements. In this paper, we propose a multi-camera time-of-flight system based on dynamic time-division multiple access (dynamic TDMA) to avoid any interference. The time synchronization is implemented optically, so that no further time synchronization, external to the cameras, is required. To achieve a high frame rate, every camera is extended with a photodiode, signaling a free channel. A synchronization protocol is implemented to allow for an autonomous operation of the ToF cameras.

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“…Disadvantages of ToF cameras are lower resolution, susceptibility to multiple reflections, interference from sunlight, and interference from other ToF cameras operating nearby, often used as multicamera setups to increase the field of view and to overcome occlusion and the lower resolution limitations [1]- [11]. Light interference in multi-ToF camera setups may result in distance calculation errors [10]- [15].…”

Section: Introductionmentioning

confidence: 99%

Optical Synchronization of Multiple Time-of-Flight Cameras Implementing TDMA

2020

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Time-of-Flight (ToF) cameras are a promising alternative to current 3-D imaging systems. A setup of multiple ToF cameras is used to overcome their comparatively lower resolution, increase the field of view, and to reduce occlusion. However, the simultaneous operation introduces the possibility of interference resulting in erroneous depth measurements. One option to mitigate interference is the consecutive arrangement of multiple cameras in time slots, such that each camera illuminates the scene exclusively, a procedure known as time division multiple access (TDMA). Instead of requiring a master synchronizing device, an approach is presented requiring no additional hardware or infrastructure to utilize TDMA by adding a synchronization software procedure to the camera's firmware. It effectively enables a camera to sense the acquisition process of other cameras and rapidly synchronize its acquisition times to operate without interference. During the experimental verification with three ToF cameras no interference occurred. The cameras each acquired 29 depth images per second while synchronizing themselves every 10 s. The proposed synchronization procedure implements an interference-free TDMA operation and overcomes traditional hard-wired synchronization setups, offering an easy setup and a methodology to upgrade existing systems without hardware modifications.

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Interference Model of Two Time-Of-Flight Cameras

Cited by 3 publications

References 6 publications

Probabilistic Modeling of Multicamera Interference for Time-of-Flight Sensors

Probabilistic Modeling of Multicamera Interference for Time-of-Flight Sensors

Synchronization of Multiple Time-of-Flight Cameras Using Photodiodes

Optical Synchronization of Multiple Time-of-Flight Cameras Implementing TDMA

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