scholarly journals Food Depth Estimation Using Low-Cost Mobile-Based System for Real-Time Dietary Assessment

2020 ◽  
Vol 6 (1) ◽  
pp. 1-11
Author(s):  
DMS Zaman ◽  
Md Hasan Maruf ◽  
Md Ashiqur Rahman ◽  
Jannatul Ferdousy ◽  
ASM Shihavuddin
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Public Awareness ◽  
Dietary Assessment ◽  
Time Estimation ◽  
Depth Estimation ◽  
Frame Structure ◽  
Optimum Number ◽  
Depth Sensors ◽  
Food Items

Real time estimation of nutrition intake from regular food items using mobile-based applications could be a breakthrough in creating public awareness of threats in overeating or faulty food choices. The bottleneck in implementing such systems is to effectively estimate the depths of the food items which is essential to calculate the volumes of foods. Volumes and density of food items can be used to estimate the weights of food eaten and their corresponding nutrition contents. Without specific depth sensors, it is very difficult to estimate the depth of any object from a single camera. Such sensors are equipped only in very advanced and expensive mobile devices. This work investigates the possibilities of using regular cameras to calculate the same using a specific frame structure. We proposed a controlled camera setup to acquire overlapping images of the food from different positions already calibrated to estimate the depths. The results were compared with the Kinect device’s depth measures to show the efficiency of the proposed method. We further investigated the optimum number of camera positions, their corresponding angles, and distances from the object to propose the best configuration for such a controlled system of image acquisition with regular mobile cameras. Overall the proposed method presents a low-cost solution to the depth estimation problem and opens up the possibilities for mobile-based apps for dietary assessment for various health-related problem-solving. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 6(1), Dec 2019 P 1-11

scholarly journals Estimating Illumination Direction for Augmented Reality in Real-Time by using Low-Cost Sensors

2017 ◽  
Vol 17 (02) ◽  
pp. e20 ◽  
Author(s):  
Kevin E. Soulier ◽  
Matías Nicolás Selzer ◽  
Martín Leonardo Larrea
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Low Cost ◽  
Time Estimation ◽  
The Real ◽  
Virtual Objects ◽  
Illumination Direction ◽  
Real Objects ◽  
Real Time Estimation ◽  
Commercial Field

In recent years, Augmented Reality has become a very popular topic, both as a research and commercial field. This trend has originated with the use of mobile devices as computational core and display. The appearance of virtual objects and their interaction with the real world is a key element in the success of an Augmented Reality software. A common issue in this type of software is the visual inconsistency between the virtual and real objects due to wrong illumination. Although illumination is a common research topic in Computer Graphics, few studies have been made about real time estimation of illumination direction. In this work we present a low-cost approach to detect the direction of the environment illumination, allowing the illumination of virtual objects according to the real light of the ambient, improving the integration of the scene. Our solution is open-source, based on Arduino hardware and the presented system was developed on Android.

scholarly journals Design and Implementation of a Low-Cost Universal RFID Wireless Logistics Terminal in the Process of Logistics Traceability

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xiaosheng Yu ◽  
Zhili Wang
Keyword(s):  
Real Time ◽  
Product Information ◽  
Local Area Network ◽  
Low Cost ◽  
Frame Structure ◽  
Area Network ◽  
Uhf Rfid ◽  
Rf Transceiver ◽  
Traceability System ◽  
Reader System

The logistics traceability system can cover the whole process of the product from the source of production to the consumption cycle. By distinguishing the key nodes of the product in the logistics sales process, the data information of the production and storage of the corresponding product is collected and entered at the corresponding node, so that the entire process is visible and controllable. On the basis of determining the overall system plan, this paper designs and develops the UHF RFID reader system and traceability system platform. In terms of the reader system, by analyzing its core functions and performance index requirements, the overall design scheme and frame structure of the reader system’s software and hardware are determined. The main control circuit is based on the STM32F103RET6 single-chip microcomputer; the RF transceiver circuit is based on the MagicRF M100. Simultaneously, we design a variety of communication circuits including LoRa and RJ45 to facilitate wireless communication with the traceability platform. In terms of software, through the research and analysis of the EPC Class-1 Generation-2 protocol standard, the multitag anticollision algorithm—Q algorithm—is adopted. This algorithm has the advantages of high recognition efficiency and a large number of successfully recognized tags per unit time. According to the design plan, the system is wirelessly networked in the B/S mode and the product information collected through RFID technology is transmitted to the management level to dynamically understand the information dynamics of logistics in real time. Using radio frequency, computer network, communication, and other technologies, the hardware and software systems of the system are integrated. The performance indicators of the hardware system are tested through experiments, and the design indicators are compared to prove the feasibility of the equipment application. After setting up the local area network and configuring the server configuration, the traceability system was accessed and the verification of the basic functions of the system was completed. The test results show that the low-cost universal RFID wireless logistics terminal has high accuracy and real-time performance in the process of logistics traceability.

scholarly journals A Body Tracking-Based Low-Cost Solution for Monitoring Workers’ Hygiene Best Practices during Pandemics

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6149
Author(s):  
Vito M. Manghisi ◽  
Michele Fiorentino ◽  
Antonio Boccaccio ◽  
Michele Gattullo ◽  
Giuseppe L. Cascella ◽  
...  
Keyword(s):  
Best Practices ◽  
Real Time ◽  
Disease Transmission ◽  
Low Cost ◽  
Emerging Infectious Diseases ◽  
Significant Risk ◽  
Prototype System ◽  
Depth Sensors ◽  
Body Tracking ◽  
Imminent Threat

Since its beginning at the end of 2019, the pandemic spread of the severe acute respiratory syndrome coronavirus 2 (Sars-CoV-2) caused more than one million deaths in only nine months. The threat of emerging and re-emerging infectious diseases exists as an imminent threat to human health. It is essential to implement adequate hygiene best practices to break the contagion chain and enhance society preparedness for such critical scenarios and understand the relevance of each disease transmission route. As the unconscious hand–face contact gesture constitutes a potential pathway of contagion, in this paper, the authors present a prototype system based on low-cost depth sensors able to monitor in real-time the attitude towards such a habit. The system records people’s behavior to enhance their awareness by providing real-time warnings, providing for statistical reports for designing proper hygiene solutions, and better understanding the role of such route of contagion. A preliminary validation study measured an overall accuracy of 91%. A Cohen’s Kappa equal to 0.876 supports rejecting the hypothesis that such accuracy is accidental. Low-cost body tracking technologies can effectively support monitoring compliance with hygiene best practices and training people in real-time. By collecting data and analyzing them with respect to people categories and contagion statistics, it could be possible to understand the importance of this contagion pathway and identify for which people category such a behavioral attitude constitutes a significant risk.

scholarly journals Real-time Estimation of Road Surfaces using Fast Monocular Depth Estimation and Normal Vector Clustering

2021 ◽  
Vol 5 (3) ◽  
pp. 206
Author(s):  
Chuho Yi ◽  
Jungwon Cho
Keyword(s):  
Real Time ◽  
Autonomous Vehicle ◽  
Depth Map ◽  
Time Estimation ◽  
Weather Conditions ◽  
Depth Estimation ◽  
Normal Vector ◽  
Single Camera ◽  
Distance Information ◽  
Lower Accuracy

Estimating a road surface or planes for applying AR(Augmented Reality) or an autonomous vehicle using a camera requires significant computation. Vision sensors have lower accuracy in distance measurement than other types of sensor, and have the difficulty that additional algorithms for estimating data must be included. However, using a camera has the advantage of being able to extract various information such as weather conditions, sign information, and road markings that are difficult to measure with other sensors. Various methods differing in sensor type and configuration have been applied. Many of the existing studies had generally researched by performing the depth estimation after the feature extraction. However, recent studies have suggested using deep learning to skip multiple processes and use a single DNN(Deep Neural Network). Also, a method using a limited single camera instead of a method using a plurality of sensors has been proposed. This paper presents a single-camera method that performs quickly and efficiently by employing a DNN to extract distance information using a single camera, and proposes a modified method for using a depth map to obtain real-time surface characteristics. First, a DNN is used to estimate the depth map, and then for quick operation, normal vector that can connect similar planes to depth is calculated, and a clustering method that can be connected is provided. An experiment is used to show the validity of our method, and to evaluate the calculation time.

scholarly journals View Synthesis: LiDAR Camera versus Depth Estimation

2021 ◽  
Author(s):  
Yupeng Xie ◽  
Sarah Fachada ◽  
Daniele Bonatto ◽  
Mehrdad Teratani ◽  
Gauthier Lafruit
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Depth Map ◽  
Depth Estimation ◽  
View Synthesis ◽  
Depth Image ◽  
Estimation Methods ◽  
Quality Performance ◽  
Virtual View ◽  
Multiview Images

Depth-Image-Based Rendering (DIBR) can synthesize a virtual view image from a set of multiview images and corresponding depth maps. However, this requires an accurate depth map estimation that incurs a high compu- tational cost over several minutes per frame in DERS (MPEG-I’s Depth Estimation Reference Software) even by using a high-class computer. LiDAR cameras can thus be an alternative solution to DERS in real-time DIBR ap- plications. We compare the quality of a low-cost LiDAR camera, the Intel Realsense LiDAR L515 calibrated and configured adequately, with DERS using MPEG-I’s Reference View Synthesizer (RVS). In IV-PSNR, the LiDAR camera reaches 32.2dB view synthesis quality with a 15cm camera baseline and 40.3dB with a 2cm baseline. Though DERS outperforms the LiDAR camera with 4.2dB, the latter provides a better quality-performance trade- off. However, visual inspection demonstrates that LiDAR’s virtual views have even slightly higher quality than with DERS in most tested low-texture scene areas, except for object borders. Overall, we highly recommend using LiDAR cameras over advanced depth estimation methods (like DERS) in real-time DIBR applications. Neverthe- less, this requires delicate calibration with multiple tools further exposed in the paper.

scholarly journals Development of a new expendable probe for the study of pelagic ecosystems from voluntary observing ships

Ocean Science ◽  
2007 ◽  
Vol 3 (2) ◽  
pp. 311-320 ◽  
Author(s):  
M. Marcelli ◽  
A. Di Maio ◽  
D. Donis ◽  
U. Mainardi ◽  
G. M. R. Manzella
Keyword(s):  
Real Time ◽  
Quantitative Estimation ◽  
Low Cost ◽  
Marine Ecosystem ◽  
Time Estimation ◽  
Cost Effective ◽  
Electronic System ◽  
Spatial And Temporal Variability ◽  
Fluorescence Measurement

Abstract. Physical and biological processes of the marine ecosystem have a high spatial and temporal variability, whose study is possible only through high resolution and synoptic observations. The Temperature and Fluorescence Launchable Probe was charted in order to answer to the claim of a cost effective temperature and fluorescence expendable profiler, to be used in ships of opportunity. The development of the expendable fluorometer has followed similar concepts of the XBT (a wire conducting the signal to a computer card), but differently from the latter it was developed with an electronic system which can be improved and adapted to several variables measure channels. To reach the aim of a low-cost probe, were utilized commercial components: a glass bulb temperature resistor for the temperature measurement, blue LEDs, a photodiode and available selective glass filters, for the fluorescence measurement. The measurement principle employed to detect phytoplankton's biomass is the active fluorescence. This method is an in vivo chlorophyll estimation, that can get the immediate biophysical reaction of phytoplankton inside the aquatic environment; it is a non-disruptive method which gives real time estimation and avoids the implicit errors due to the manipulation of samples. The possibility of using a continuous profiling probe, with an active fluorescence measurement, is very important in real time phytoplankton's study; it is the best way to follow the variability of sea productivity. In fact, because of the high time and space variability of phytoplankton, due to its capability to answer in a relatively short time to ecological variations in its environment and because of its characteristic patchiness, there isn't a precise quantitative estimation of the biomass present in the Mediterranean Sea.

scholarly journals DISTq: Low-cost, accurate and real-time estimation of insulin sensitivity

2009 ◽  
Vol 42 (12) ◽  
pp. 91-96
Author(s):  
Paul D. Docherty ◽  
J. Geoffrey Chase ◽  
Thomas F. Lotz ◽  
Christopher E. Hann ◽  
Geoffrey M. Shaw ◽  
...  
Keyword(s):  
Insulin Sensitivity ◽  
Real Time ◽  
Low Cost ◽  
Time Estimation ◽  
Real Time Estimation
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