Real-Time Human Detection Based on the Improved Local Binary Pattern

2014 ◽  
Vol 1044-1045 ◽  
pp. 1246-1250
Author(s):  
Dong Mei Wu ◽  
Xing Ma ◽  
Jing Wang ◽  
Hao Zhang
Keyword(s):  
Real Time ◽  
Local Binary Pattern ◽  
Human Detection ◽  
Computational Method ◽  
Detection Accuracy ◽  
Real Time System ◽  
Feature Vectors ◽  
Linear Classifier ◽  
Detection Window ◽  
Testing Speed

By analyzing the detection accuracy and the testing speed of the Local Binary Pattern. we propose an improved LBP algorithm and apply it in human detection. Through the signs of the comparisons among neighboring pixels, it will get the histogram of the detection window. Then we can encode the global contour by the distribution coefficient of the histogram. when the Linear classifier is used, we propose a fast computational method that does not need to explicitly generate feature vectors and not require feature vectors normalization. experiment shows that this method has higher efficiency and can’t reduce the accuracy, it achieves 19 fps speed and can be used in a real-time system.

A Fast Algorithm Detection for Barcode Inclination Defect

2014 ◽  
Vol 644-650 ◽  
pp. 1172-1175
Author(s):  
Ya Li Qi ◽  
Ye Li Li ◽  
Cui Wang ◽  
Li Kun Lu
Keyword(s):  
Real Time ◽  
Fast Algorithm ◽  
The Other ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Time System ◽  
Real Time System ◽  
The Real ◽  
Online System ◽  
Real Time Detection

Barcode detection has many applications and detection methods. Most applications have their own requirements for detection accuracy and speed. This paper has its requirement for speed in the real time system to detection inclination defect of barcode. It predominantly researches on two algorithms and their applications on 1-dimentional barcode scanning. One is location and the other is angle of inclination. The algorithms are particularly useful for real time detection of barcodes in online system with image vision devices.

scholarly journals Real Time Human Detection and Localization Using Consumer Grade Camera and Commercial UAV

2018 ◽  
Author(s):  
Nemi Bhattarai ◽  
Tai Nakamura ◽  
Chitrini Mozumder
Keyword(s):  
Real Time ◽  
Computation Time ◽  
Google Earth ◽  
Human Detection ◽  
Flying Height ◽  
Detection Accuracy ◽  
Localization Accuracy ◽  
Size Relationship ◽  
Video Frames ◽  
Uav Images

Human detection from Unmanned Aerial Vehicles (UAV) is gaining popularity in the field of disaster management, crowd counting, people monitoring. Real time human detection from UAV is a challenging task, because of many constraints involved. This study proposes a system for real time detection of humans on videos captured from UAVs addressing three of these constraints namely, flying height, computation time and scale of viewing. The proposed method integrated an android application with a binary classifier based on Haar-features to automatically detect human / non-human class from UAV images. The video frames were parsed and detected humans from image frames were geo-localized and visualized on Google Earth. The performance was evaluated for geo-localization accuracy, computation time and detection accuracy, considering human coverage – pixel size relationship for various heights and scale factor. Based on flying height - human size relationship and tradeoff between detection accuracy vs computation time, the study came up with optimal parameters for OpenCV’s cv2.cascadeClassifier. detectMultiScale function. This paper establishes a strong ground for further research relating to real time human detection from UAV.

Real-Time System for Sending Data from Three Clients to One Server with MATLAB

2015 ◽  
Vol 2 (1) ◽  
pp. 35-41
Author(s):  
Rivan Risdaryanto ◽  
Houtman P. Siregar ◽  
Dedy Loebis
Keyword(s):  
Information System ◽  
Real Time ◽  
Time System ◽  
Real Time System ◽  
The Real ◽  
Performance Time ◽  
Data Process ◽  
Effectiveness And Efficiency

The real-time system is now used on many fields, such as telecommunication, military, information system, evenmedical to get information quickly, on time and accurate. Needless to say, a real-time system will always considerthe performance time. In our application, we define the time target/deadline, so that the system should execute thewhole tasks under predefined deadline. However, if the system failed to finish the tasks, it will lead to fatal failure.In other words, if the system cannot be executed on time, it will affect the subsequent tasks. In this paper, wepropose a real-time system for sending data to find effectiveness and efficiency. Sending data process will beconstructed in MATLAB and sending data process has a time target as when data will send.

The Goal-Setting Model in a Multiagent Hard Real-Time System

Vestnik MEI ◽  
2018 ◽  
Vol 5 (5) ◽  
pp. 73-78
Author(s):  
Igor В. Fominykh ◽  
◽  
Sergey V. Romanchuk ◽  
Nikolay Р. Alekseev ◽  
◽  
...  
Keyword(s):  
Real Time ◽  
Goal Setting ◽  
Time System ◽  
Real Time System ◽  
Hard Real Time

Design of Preliminary Experiments with the Sun Java Real-Time System

2006 ◽  
Author(s):  
T. S. Cook ◽  
D. Drusinsky ◽  
J. B. Michael ◽  
T. W. Otani ◽  
M. Shing
Keyword(s):  
Real Time ◽  
The Sun ◽  
Time System ◽  
Real Time System

scholarly journals Power-Based Non-Intrusive Condition Monitoring for Terminal Device in Smart Grid

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3635 ◽  
Author(s):  
Guoming Zhang ◽  
Xiaoyu Ji ◽  
Yanjie Li ◽  
Wenyuan Xu
Keyword(s):  
Smart Grid ◽  
Power Consumption ◽  
Real Time ◽  
Condition Monitoring ◽  
Resource Constraints ◽  
Detection System ◽  
Stable Operation ◽  
Detection Accuracy ◽  
Monitoring Method ◽  
Dsp Processors

As a critical component in the smart grid, the Distribution Terminal Unit (DTU) dynamically adjusts the running status of the entire smart grid based on the collected electrical parameters to ensure the safe and stable operation of the smart grid. However, as a real-time embedded device, DTU has not only resource constraints but also specific requirements on real-time performance, thus, the traditional anomaly detection method cannot be deployed. To detect the tamper of the program running on DTU, we proposed a power-based non-intrusive condition monitoring method that collects and analyzes the power consumption of DTU using power sensors and machine learning (ML) techniques, the feasibility of this approach is that the power consumption is closely related to the executing code in CPUs, that is when the execution code is tampered with, the power consumption changes accordingly. To validate this idea, we set up a testbed based on DTU and simulated four types of imperceptible attacks that change the code running in ARM and DSP processors, respectively. We generate representative features and select lightweight ML algorithms to detect these attacks. We finally implemented the detection system on the windows and ubuntu platform and validated its effectiveness. The results show that the detection accuracy is up to 99.98% in a non-intrusive and lightweight way.

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