Pseudonoise Optical Modulation for Real-Time 3-D Imaging With Minimum Interference

Büttgen, Bernhard; Mechat, M'h.-A. El; Lustenberger, Felix; Seitz, Peter

doi:10.1109/tcsi.2007.904598

Cited by 40 publications

(18 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Calculations on distance noise from measurement noise has been reported previously for the case of pulsed TOF [3,6] and for phased TOF [6][7][8]. The expressions vary somewhat, but show the same dependencies on pulse duration and signal levels.…”

Section: Introductionmentioning

confidence: 79%

See 1 more Smart Citation

Design tool for TOF and SL based 3D cameras

et al. 2017

View full text Add to dashboard Cite

Active illumination 3D imaging systems based on Time-of-flight (TOF) and Structured Light (SL) projection are in rapid development, and are constantly finding new areas of application. In this paper, we present a theoretical design tool that allows prediction of 3D imaging precision. Theoretical expressions are developed for both TOF and SL imaging systems. The expressions contain only physically measurable parameters and no fitting parameters. We perform 3D measurements with both TOF and SL imaging systems, showing excellent agreement between theoretical and measured distance precision. The theoretical framework can be a powerful 3D imaging design tool, as it allows for prediction of 3D measurement precision already in the design phase.

show abstract

Section: Introductionmentioning

confidence: 79%

“…The expressions vary somewhat, but show the same dependencies on pulse duration and signal levels. Comparison against experimental results has been shown for pulsed TOF [3] and for phased TOF [8]. For structured light, some work on noise calculations can be found, e.g [9,10].…”

Section: Introductionmentioning

confidence: 96%

Design tool for TOF and SL based 3D cameras

et al. 2017

View full text Add to dashboard Cite

show abstract

“…The use of PN modulation with T c < T d has been demonstrated in TOF cameras, 9,10 however this method has serious drawbacks. The precision is proportional to the modulation frequency of the light source, as described in section 1.1.…”

Section: Pseudo-noise Modulationmentioning

confidence: 99%

Multiple range imaging camera operation with minimal performance impact

et al. 2010

View full text Add to dashboard Cite

Time-of-flight range imaging cameras operate by illuminating a scene with amplitude modulated light and measuring the phase shift of the modulation envelope between the emitted and reflected light. Object distance can then be calculated from this phase measurement. This approach does not work in multiple camera environments as the measured phase is corrupted by the illumination from other cameras. To minimize inaccuracies in multiple camera environments, replacing the traditional cyclic modulation with pseudo-noise amplitude modulation has been previously demonstrated. However, this technique effectively reduced the modulation frequency, therefore decreasing the distance measurement precision (which has a proportional relationship with the modulation frequency). A new modulation scheme using maximum length pseudo-random sequences binary phase encoded onto the existing cyclic amplitude modulation, is presented. The effective modulation frequency therefore remains unchanged, providing range measurements with high precision. The effectiveness of the new modulation scheme was verified using a custom time-of-flight camera based on the PMD19-K2 range imaging sensor. The new pseudo-noise modulation has no significant performance decrease in a single camera environment. In a two camera environment, the precision is only reduced by the increased photon shot noise from the second illumination source.

show abstract

“…One appealing way to measure depth is to use a time-of-flight (TOF) camera, which obtains dense depth measurements by emitting pulses of light and measuring their round trip times [1]. However, for reasons that range from system power constraints to the mitigation of multi-camera interference, the frame rate at which accurate depth measurements can be acquired is often reduced [2,3,4]. To address this issue, we present an approach that uses concurrently collected images and previous depth measurements to estimate depth as shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Depth Estimation of Non-Rigid Objects for Time-Of-Flight Imaging

Noraky

Sze

2018

2018 25th IEEE International Conference on Image Processing (ICIP)

View full text Add to dashboard Cite

Depth sensing is useful for a variety of applications that range from augmented reality to robotics. Time-of-flight (TOF) cameras are appealing because they obtain dense depth measurements with low latency. However, for reasons ranging from power constraints to multi-camera interference, the frequency at which accurate depth measurements can be obtained is reduced. To address this, we propose an algorithm that uses concurrently collected images to estimate the depth of non-rigid objects without using the TOF camera. Our technique models non-rigid objects as locally rigid and uses previous depth measurements along with the optical flow of the images to estimate depth. In particular, we show how we exploit the previous depth measurements to directly estimate pose and how we integrate this with our model to estimate the depth of non-rigid objects by finding the solution to a sparse linear system. We evaluate our technique on a RGB-D dataset of deformable objects, where we estimate depth with a mean relative error of 0.37% and outperform other adapted techniques.

show abstract

Pseudonoise Optical Modulation for Real-Time 3-D Imaging With Minimum Interference

Cited by 40 publications

References 14 publications

Design tool for TOF and SL based 3D cameras

Design tool for TOF and SL based 3D cameras

Multiple range imaging camera operation with minimal performance impact

Depth Estimation of Non-Rigid Objects for Time-Of-Flight Imaging

Contact Info

Product

Resources

About