scholarly journals 3-D People Counting with a Stereo Camera on GPU Embedded Board

2018 ◽  
Vol 8 (11) ◽  
pp. 2017 ◽  
Author(s):  
Gyu-cheol Lee ◽  
Sang-ha Lee ◽  
Jisang Yoo
Keyword(s):  
Real Time ◽  
Stereo Matching ◽  
Depth Image ◽  
Depth Information ◽  
People Detection ◽  
Real Time Processing ◽  
Stereo Camera ◽  
People Counting ◽  
Time Operation ◽  
Real Time Operation

People counting in surveillance cameras is a key technology for understanding the flow population and generating heat maps. In recent years, people detection performance has been greatly improved with the development of object detection algorithms using deep learning. However, in places where people are crowded, the detection rate is low as people are often occluded by other people. We proposed a people-counting method using a stereo camera to resolve the non-detection problem due to the occlusion. We applied stereo matching to extract the depth image and convert the camera view to top view using depth information. People were detected using a height map and an occupancy map, and people were tracked and counted using a Kalman filter-based tracker. We operated the proposed method on the NVIDIA Jetson TX2 to check the real-time operation possibility on the embedded board. Experimental results showed that the proposed method had higher accuracy than the existing methods and that real-time processing is possible.

scholarly journals A Residual Network and FPGA Based Real-Time Depth Map Enhancement System

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 546
Author(s):  
Zhenni Li ◽  
Haoyi Sun ◽  
Yuliang Gao ◽  
Jiao Wang
Keyword(s):  
Real Time ◽  
Super Resolution ◽  
Depth Map ◽  
Acquisition System ◽  
Depth Image ◽  
Fpga Design ◽  
Depth Sensing ◽  
Residual Network ◽  
Real Time Processing ◽  
Depth Maps

Depth maps obtained through sensors are often unsatisfactory because of their low-resolution and noise interference. In this paper, we propose a real-time depth map enhancement system based on a residual network which uses dual channels to process depth maps and intensity maps respectively and cancels the preprocessing process, and the algorithm proposed can achieve real-time processing speed at more than 30 fps. Furthermore, the FPGA design and implementation for depth sensing is also introduced. In this FPGA design, intensity image and depth image are captured by the dual-camera synchronous acquisition system as the input of neural network. Experiments on various depth map restoration shows our algorithms has better performance than existing LRMC, DE-CNN and DDTF algorithms on standard datasets and has a better depth map super-resolution, and our FPGA completed the test of the system to ensure that the data throughput of the USB 3.0 interface of the acquisition system is stable at 226 Mbps, and support dual-camera to work at full speed, that is, 54 fps@ (1280 × 960 + 328 × 248 × 3).

Real-Time Operation and Characterization of a High-Performance Time-Based Accelerometer

2015 ◽  
Vol 24 (6) ◽  
pp. 1703-1711 ◽  
Author(s):  
Rosana Alves Dias ◽  
Filipe Serra Alves ◽  
Margaret Costa ◽  
Helder Fonseca ◽  
Jorge Cabral ◽  
...  
Keyword(s):  
Real Time ◽  
High Performance ◽  
Performance Time ◽  
Time Operation ◽  
Real Time Operation

Cultural Change in ALS Real Time Operation and Optimization in Vaca Muerta Through CWE

2018 ◽  
Author(s):  
J. I. Alvarez Claramunt ◽  
P. E. Bizzotto ◽  
F. Sapag ◽  
E. Ferrigno ◽  
J. L. Barros ◽  
...  
Keyword(s):  
Real Time ◽  
Cultural Change ◽  
Time Operation ◽  
Vaca Muerta ◽  
Real Time Operation

scholarly journals TDOA-based microwave imaging algorithm for real-time microwave ablation monitoring

2017 ◽  
Vol 10 (2) ◽  
pp. 169-178 ◽  
Author(s):  
Shouhei Kidera ◽  
Luz Maria Neira ◽  
Barry D. Van Veen ◽  
Susan C. Hagness
Keyword(s):  
Real Time ◽  
Microwave Ablation ◽  
Microwave Imaging ◽  
Ablation Zone ◽  
Real Time Monitoring ◽  
Imaging Algorithm ◽  
Array Measurements ◽  
Time Operation ◽  
Real Time Operation ◽  
Propagation Media

Microwave ablation is widely recognized as a promising minimally invasive tool for treating cancer. Real-time monitoring of the dimensions of the ablation zone is indispensable for ensuring an effective and safe treatment. In this paper, we propose a microwave imaging algorithm for monitoring the evolution of the ablation zone. Our proposed algorithm determines the boundary of the ablation zone by exploiting the time difference of arrival (TDOA) between signals received before and during the ablation at external antennas surrounding the tissue, using the interstitial ablation antenna as the transmitter. A significant advantage of this method is that it requires few assumptions about the dielectric properties of the propagation media. Also the simplicity of the signal processing, wherein the TDOA is determined from a cross-correlation calculation, allows real-time monitoring and provides robust performance in the presence of noise. We investigate the performance of this approach for the application of breast tumor ablation. We use simulated array measurements obtained from finite-difference time-domain simulations of magnetic resonance imaging-derived numerical breast phantoms. The results demonstrate that our proposed method offers the potential to achieve millimeter-order accuracy and real-time operation in estimating the boundary of the ablation zone in heterogeneous and dispersive breast tissue.

scholarly journals SoC-FPGA systems for the acquisition and processing of electroencephalographic signals

2021 ◽  
Vol 10 (3) ◽  
pp. 237
Author(s):  
Matias Javier Oliva ◽  
Pablo Andrés García ◽  
Enrique Mario Spinelli ◽  
Alejandro Luis Veiga
Keyword(s):  
Embedded System ◽  
Real Time ◽  
General Purpose ◽  
System Response ◽  
Single Chip ◽  
Real Time Processing ◽  
General Purpose Processor ◽  
Time Operation ◽  
Electroencephalographic Signals ◽  
High Level

<span lang="EN-US">Real-time acquisition and processing of electroencephalographic signals have promising applications in the implementation of brain-computer interfaces. These devices allow the user to control a device without performing motor actions, and are usually made up of a biopotential acquisition stage and a personal computer (PC). This structure is very flexible and appropriate for research, but for final users it is necessary to migrate to an embedded system, eliminating the PC from the scheme. The strict real-time processing requirements of such systems justify the choice of a system on a chip field-programmable gate arrays (SoC-FPGA) for its implementation. This article proposes a platform for the acquisition and processing of electroencephalographic signals using this type of device, which combines the parallelism and speed capabilities of an FPGA with the simplicity of a general-purpose processor on a single chip. In this scheme, the FPGA is in charge of the real-time operation, acquiring and processing the signals, while the processor solves the high-level tasks, with the interconnection between processing elements solved by buses integrated into the chip. The proposed scheme was used to implement a brain-computer interface based on steady-state visual evoked potentials, which was used to command a speller. The first tests of the system show that a selection time of 5 seconds per command can be achieved. The time delay between the user’s selection and the system response has been estimated at 343 µs.</span>

scholarly journals CONTROLLING AND MONITORING OF AUTOMATION WATER SUPPLY SYSTEM BASED ON IOT WITH THEFT IDENTIFICATION

2017 ◽  
Vol 5 (5) ◽  
pp. 320-325
Author(s):  
Ahmad T. Jaiad ◽  
Hamzah Sabr Ghayyib
Keyword(s):  
Water Supply ◽  
Real Time ◽  
Water Conservation ◽  
Water Distribution ◽  
Network Connectivity ◽  
Raspberry Pi ◽  
Human Beings ◽  
Residential Areas ◽  
Time Operation ◽  
Real Time Operation

Water is the most precious and valuable because it’s a basic need of all the human beings but, now a day water supply department are facing problem in real time operation this is because less amount of water in resources due to less rain fall. With increase in Population, urban residential areas have increased because of this reasons water has become a crucial problem which affects the problem of water distribution, interrupted water supply, water conservation, water consumption and also the water quality so, to overcome water supply related problems and make system efficient there is need of proper monitoring and controlling system. In this project, we are focusing on continuous and real time monitoring of water supply in IOT platform. Water supply with continuous monitoring makes a proper distribution so that, we can have a record of available amount of water in tanks, flow rate, abnormality in distribution line. Internet of things is nothing but the network of physical objects embedded with electronics, sensors, software, and network connectivity. Monitoring can be done from anywhere as central office. Using Adafruit as free sever data continuously pushed on cloud so we can see data in real time operation. Using different sensors with controller and raspberry pi as Mini computer can monitor data and also control operation from cloud with efficient client server communication.

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