Analysis of RGB-D camera technologies for supporting different facial usage scenarios

Ulrich, Luca; Vezzetti, Enrico; Moos, Sandro; Marcolin, Federica

doi:10.1007/s11042-020-09479-0

Cited by 34 publications

(13 citation statements)

References 74 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The active mode of Intel D435 adopts an infrared radiation (IR) laser projector to generate the laser speckle patterns [ 4 ]. It performs better than other methods for face identification and face expression recognition as reported by Luca et al [ 5 ]. The accuracies of ASV and SL are higher than those of TOF and PSV.…”

Section: Introductionmentioning

confidence: 74%

3D Reconstruction with Single-Shot Structured Light RGB Line Pattern

Wang

2021

Sensors

View full text Add to dashboard Cite

Single-shot 3D reconstruction technique is very important for measuring moving and deforming objects. After many decades of study, a great number of interesting single-shot techniques have been proposed, yet the problem remains open. In this paper, a new approach is proposed to reconstruct deforming and moving objects with the structured light RGB line pattern. The structured light RGB line pattern is coded using parallel red, green, and blue lines with equal intervals to facilitate line segmentation and line indexing. A slope difference distribution (SDD)-based image segmentation method is proposed to segment the lines robustly in the HSV color space. A method of exclusion is proposed to index the red lines, the green lines, and the blue lines respectively and robustly. The indexed lines in different colors are fused to obtain a phase map for 3D depth calculation. The quantitative accuracies of measuring a calibration grid and a ball achieved by the proposed approach are 0.46 and 0.24 mm, respectively, which are significantly lower than those achieved by the compared state-of-the-art single-shot techniques.

show abstract

Section: Introductionmentioning

confidence: 74%

3D Reconstruction with Single-Shot Structured Light RGB Line Pattern

Wang

2021

Sensors

View full text Add to dashboard Cite

show abstract

“… 32 , 33 Ulrich et al. 34 provided a comprehensive review of these emerging methods and other RGB-D sensing technologies.…”

Section: System Interface Designmentioning

confidence: 99%

Smartphone-based imaging systems for medical applications: a critical review

2021

View full text Add to dashboard Cite

. Significance: Smartphones come with an enormous array of functionality and are being more widely utilized with specialized attachments in a range of healthcare applications. A review of key developments and uses, with an assessment of strengths/limitations in various clinical workflows, was completed. Aim: Our review studies how smartphone-based imaging (SBI) systems are designed and tested for specialized applications in medicine and healthcare. An evaluation of current research studies is used to provide guidelines for improving the impact of these research advances. Approach: First, the established and emerging smartphone capabilities that can be leveraged for biomedical imaging are detailed. Then, methods and materials for fabrication of optical, mechanical, and electrical interface components are summarized. Recent systems were categorized into four groups based on their intended application and clinical workflow: ex vivo diagnostic, in vivo diagnostic, monitoring, and treatment guidance. Lastly, strengths and limitations of current SBI systems within these various applications are discussed. Results: The native smartphone capabilities for biomedical imaging applications include cameras, touchscreens, networking, computation, 3D sensing, audio, and motion, in addition to commercial wearable peripheral devices. Through user-centered design of custom hardware and software interfaces, these capabilities have the potential to enable portable, easy-to-use, point-of-care biomedical imaging systems. However, due to barriers in programming of custom software and on-board image analysis pipelines, many research prototypes fail to achieve a prospective clinical evaluation as intended. Effective clinical use cases appear to be those in which handheld, noninvasive image guidance is needed and accommodated by the clinical workflow. Handheld systems for in vivo , multispectral, and quantitative fluorescence imaging are a promising development for diagnostic and treatment guidance applications. Conclusions: A holistic assessment of SBI systems must include interpretation of their value for intended clinical settings and how their implementations enable better workflow. A set of six guidelines are proposed to evaluate appropriateness of smartphone utilization in terms of clinical context, completeness, compactness, connectivity, cost, and claims. Ongoing work should prioritize realistic clinical assessments with quantitative and qualitative comparison to non-smartphone systems to clearly demonstrate the value of smartphone-based systems. Improved hardware design to accommodate the rapidly changing smartphone ecosystem, creation of open-source image acquisition and analysis pipelines, and adoption of robust calibration techniques to address phone-to-phone variability are three high priority areas to move SBI research forwar...

show abstract

“…3D or RGB-D cameras provide two types of co-registered data covering a similar field of view: imagery (RGB) and range or depth (D) data. Ulrich et al [14] provide a good overview of the different RGB-D camera and depth estimation technologies, including passive stereoscopy, structed light, time-of-flight (ToF), and active stereoscopy [14]. Low-cost depth and RGB-D cameras have been widely researched for various close-range applications in indoor environments.…”

Section: Low-cost 3d Sensors and Applicationsmentioning

confidence: 99%

Outdoor Mobile Mapping and AI-Based 3D Object Detection with Low-Cost RGB-D Cameras: The Use Case of On-Street Parking Statistics

et al. 2021

View full text Add to dashboard Cite

A successful application of low-cost 3D cameras in combination with artificial intelligence (AI)-based 3D object detection algorithms to outdoor mobile mapping would offer great potential for numerous mapping, asset inventory, and change detection tasks in the context of smart cities. This paper presents a mobile mapping system mounted on an electric tricycle and a procedure for creating on-street parking statistics, which allow government agencies and policy makers to verify and adjust parking policies in different city districts. Our method combines georeferenced red-green-blue-depth (RGB-D) imagery from two low-cost 3D cameras with state-of-the-art 3D object detection algorithms for extracting and mapping parked vehicles. Our investigations demonstrate the suitability of the latest generation of low-cost 3D cameras for real-world outdoor applications with respect to supported ranges, depth measurement accuracy, and robustness under varying lighting conditions. In an evaluation of suitable algorithms for detecting vehicles in the noisy and often incomplete 3D point clouds from RGB-D cameras, the 3D object detection network PointRCNN, which extends region-based convolutional neural networks (R-CNNs) to 3D point clouds, clearly outperformed all other candidates. The results of a mapping mission with 313 parking spaces show that our method is capable of reliably detecting parked cars with a precision of 100% and a recall of 97%. It can be applied to unslotted and slotted parking and different parking types including parallel, perpendicular, and angle parking.

show abstract

Analysis of RGB-D camera technologies for supporting different facial usage scenarios

Cited by 34 publications

References 74 publications

3D Reconstruction with Single-Shot Structured Light RGB Line Pattern

3D Reconstruction with Single-Shot Structured Light RGB Line Pattern

Smartphone-based imaging systems for medical applications: a critical review

Outdoor Mobile Mapping and AI-Based 3D Object Detection with Low-Cost RGB-D Cameras: The Use Case of On-Street Parking Statistics

Contact Info

Product

Resources

About