A Research on Real-Time Hand-Detection Technology Oriented to the Somatic Games

2013 ◽  
Vol 748 ◽  
pp. 999-1002 ◽  
Author(s):  
Ren Chen ◽  
Hui Li
Keyword(s):  
Real Time ◽  
Failure Rate ◽  
Skin Color ◽  
Detection Rate ◽  
Detection Method ◽  
Hand Detection ◽  
Key Technology ◽  
Video Frames ◽  
Detection Technology ◽  
Adaboost Classifier

Hand-detection is a key technology to the somatic games. In this paper, we present a real-time hand-detection method based on Adaboost and skin-color characteristic. By processing the video frames with Adaboost classifier, we abstract the target regions which may contain the hand gestures. Then a filter based on skin color is proposed to select the correct regions. The best detection rate reaches above 89% with an acceptable failure rate and misjudgment rate. Experimental results show that this method is a lightweight and rapid approach to implement real-time hand detection in somatic games.

scholarly journals A Face Detection Method Based on Skin Color Model and Improved AdaBoost Algorithm

2020 ◽  
Vol 37 (6) ◽  
pp. 929-937
Author(s):  
Xiaoying Yang ◽  
Nannan Liang ◽  
Wei Zhou ◽  
Hongmei Lu
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Detection Rate ◽  
Detection Method ◽  
Random Search ◽  
Color Space ◽  
Color Model ◽  
High Detection Rate ◽  
Adaboost Algorithm ◽  
Skin Color Model

This paper integrates skin color model and improved AdaBoost into a face detection method for high-resolution images with complex backgrounds. Firstly, the skin color areas were detected in a multi-color space. Each image was subject to adaptive brightness compensation, and converted into the YCbCr space, and a skin color model was established to solve face similarity. After eliminating the background interference by morphological method, the skin color areas were segmented to obtain the candidate face areas. Next, the inertia weight control factors and random search factor were introduced to optimize the global search ability of particle swarm optimization (PSO). The improved PSO was adopted to optimize the initial connection weights and output thresholds of the neural network. After that, a strong AdaBoost classifier was designed based on optimized weak BPNN classifiers, and the weight distribution strategy of AdaBoost was further improved. Finally, the improved AdaBoost was employed to detect the final face areas among the candidate areas. Simulation results show that our face detection method achieved high detection rate at a fast speed, and lowered false detection rate and missed detection rate.

scholarly journals The value of single-molecule real-time technology in the diagnosis of rare thalassemia variants and analysis of phenotype–genotype correlation

2021 ◽  
Author(s):  
Shiqiang Luo ◽  
Xingyuan Chen ◽  
Dingyuan Zeng ◽  
Ning Tang ◽  
Dejian Yuan ◽  
...  
Keyword(s):  
Real Time ◽  
Single Molecule ◽  
Detection Rate ◽  
Molecular Characteristics ◽  
Dot Blot ◽  
Gene Screening ◽  
Positive Detection Rate ◽  
Detection Technology ◽  
Conventional Technology ◽  
Diagnostic Technology

AbstractTo compare single-molecule real-time technology (SMRT) and conventional genetic diagnostic technology of rare types of thalassemia mutations, and to analyze the molecular characteristics and phenotypes of rare thalassemia gene variants, we used 434 cases with positive hematology screening as the cohort, then used SMRT technology and conventional gene diagnosis technology [(Gap-PCR, multiple ligation probe amplification technology (MLPA), PCR-reverse dot blot (RDB)] for thalassemia gene screening. Among the 434 enrolled cases, conventional technology identified 318 patients with variants (73.27%) and 116 patients without variants (26.73%), SMRT identified 361 patients with variants (83.18%), and 73 patients without variants (16.82%). The positive detection rate of SMRT was 9.91% higher than conventional technology. Combination of the two methods identified 485 positive alleles among 49 types of variant. The genotypes of 354 cases were concordant between the two methods, while 80 cases were discordant. Among the 80 cases, 76 cases had variants only identified in SMRT method, 3 cases had variants only identified in conventional method, and 1 false positive result by the traditional PCR detection technology. Except the three variants in HS40 and HBG1-HBG2 loci, which was beyond the design of SMRT method in this study, all the other discordant variants identified by SMRT were validated by further Sanger sequencing or MLPA. The hematological phenotypic parameters of 80 discordant cases were also analyzed. SMRT technology increased the positive detection rate of thalassemia genes, and detected rare thalassemia cases with variable phenotypes, which had great significance for clinical thalassemia gene screening.

scholarly journals Large-Aperture Real-Time Compensated Collimating Wavefront Error Detection Method

2019 ◽  
Vol 9 (11) ◽  
pp. 2370
Author(s):  
Xueliang Zhu ◽  
Dasen Wang ◽  
Fengming Nie ◽  
Bingcai Liu ◽  
Hongjun Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Error Detection ◽  
Detection Method ◽  
Three Dimensional ◽  
Surface Measurement ◽  
Dimensional Error ◽  
Detection Technology ◽  
Wavefront Error ◽  
Scanning Detection ◽  
Wavefront Detection

This paper proposes a real-time compensated pentaprism scanning wavefront detection method to achieve real-time compensation for scanning errors occurring during prism movement along a guide rail. The method is based on existing pentaprism scanning wavefront detection technology and it is realized by applying self-collimation-based three-dimensional error compensation. Using theoretical and data analyses of a detection experiment, the reliability of the optimized pentaprism scanning detection method is verified, thus effectively ensuring the reasonable estimation of the interferometry surface measurement uncertainty.

Design of Bamboo Strip Detection System Based on Labview and Matlab Mixed Programming

2013 ◽  
Vol 302 ◽  
pp. 772-775 ◽  
Author(s):  
Li Ping He ◽  
Shu Xiang Song ◽  
Lei Liu ◽  
Xian Ming Jiang
Keyword(s):  
Real Time ◽  
Detection Rate ◽  
Surface Defects ◽  
Detection System ◽  
Detection Accuracy ◽  
The Novel ◽  
Large Area ◽  
Accuracy Requirement ◽  
Detection Technology ◽  
Mixed Programming

According to the domestic situation that bamboo strip detection technology is artificial intervention and low automation, the novel automatic bamboo strip detection system is designed based on Labview and Matlab mixed programming. The real-time detection on bamboo surface defects is realized in the system such as serious damage, stripe, scratch, large area dim. Moreover, the system provides more than 92% detection accuracy and eight strips per second detection rate, both of which can meet the accuracy requirement of practical production. In general, this paper provides a new kind of method for detection system.

Development and Application of Quality Control System for Highway Subgrade Construction

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Tong Wang
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Detection Method ◽  
System Development ◽  
Effective Control ◽  
Construction Process ◽  
Development Mode ◽  
The Road ◽  
Whole Process

The compaction quality of the subgrade is directly related to the service life of the road. Effective control of the subgrade construction process is the key to ensuring the compaction quality of the subgrade. Therefore, real-time, comprehensive, rapid and accurate prediction of construction compaction quality through informatization detection method is an important guarantee for speeding up construction progress and ensuring subgrade compaction quality. Based on the function of the system, this paper puts forward the principle of system development and the development mode used in system development, and displays the development system in real-time to achieve the whole process control of subgrade construction quality.

Real-Time Line Detection Method for Camera Images of the Rescue Robot

2010 ◽  
Vol 130 (11) ◽  
pp. 2039-2046
Author(s):  
Munetoshi Numada ◽  
Masaru Shimizu ◽  
Takuma Funahashi ◽  
Hiroyasu Koshimizu
Keyword(s):  
Real Time ◽  
Detection Method ◽  
Line Detection ◽  
Time Line ◽  
Rescue Robot

Research Situation Analysis of On-line Detection Technology for Power Transformer Winding Deformation

2020 ◽  
Vol 13 (6) ◽  
pp. 823-832
Author(s):  
Zhenhua Li ◽  
Weihui Jiang ◽  
Li Qiu ◽  
Zhenxing Li ◽  
Yanchun Xu
Keyword(s):  
Detection Method ◽  
Theoretical Research ◽  
Line Detection ◽  
Response Analysis ◽  
Advantages And Disadvantages ◽  
Detection Technology ◽  
The Future ◽  
Transformer Winding ◽  
On Line ◽  
Winding Deformation

Background: Winding deformation is one of the most common faults in power transformers, which seriously threatens the safe operation of transformers. In order to discover the hidden trouble of transformer in time, it is of great significance to actively carry out the research of transformer winding deformation detection technology. Methods: In this paper, several methods of winding deformation detection with on-line detection prospects are summarized. The principles and characteristics of each method are analyzed, and the advantages and disadvantages of each method as well as the future research directions are expounded. Finally, aiming at the existing problems, the development direction of detection method for winding deformation in the future is prospected. Results: The on-line frequency response analysis method is still immature, and the vibration detection method is still in the theoretical research stage. Conclusion: The ΔV − I1 locus method provides a new direction for on-line detection of transformer winding deformation faults, which has certain application prospects and practical engineering value.

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