A Person Identification Method Using a Top-View Head Image from an Overhead Camera

2012 ◽  
Vol 16 (6) ◽  
pp. 696-703 ◽  
Author(s):  
Ryota Nakatani ◽  
◽  
Daichi Kouno ◽  
Kazutaka Shimada ◽  
Tsutomu Endo
Keyword(s):  
Body Size ◽  
Background Subtraction ◽  
Experimental Results ◽  
Hair Color ◽  
Identification Task ◽  
Person Identification ◽  
Identification Methods ◽  
Adaboost Algorithm ◽  
Identification Method ◽  
Top View

In this paper, we describe a novel image-based person identification task. Conventional face-based person identification methods have a low tolerance for occluded situations, such as overlapping of people in an image. We focus on an image from an overhead camera. Using the overhead camera reduces restrictions on the installation location of the camera and solves the problem of occluded images. First, our method identifies a person area in a captured image by using background subtraction. Then, it extracts four features from the area: (1) body size, (2) hair color, (3) hairstyle, and (4) hair whorl. We apply the four features to the AdaBoost algorithm. Experimental results show the effectiveness of our method.

Person Identification Using Top-View Image with Depth Information

2013 ◽  
Vol 1 (2) ◽  
pp. 67-79
Author(s):  
Daichi Kouno ◽  
Kazutaka Shimada ◽  
Tsutomu Endo
Keyword(s):  
Body Height ◽  
High Accuracy ◽  
Identification Accuracy ◽  
Depth Information ◽  
Identification Task ◽  
Person Identification ◽  
Identification Methods ◽  
Rich Information ◽  
Accuracy Rates ◽  
Top View

In this paper, the authors describe a novel image-based person identification task. Traditional face-based person identification methods have a low tolerance for occluded situation, such as overlapping of people in an image. The authors focus on an image from an overhead camera. The authors utilize depth information for the identification task. By using depth information, the authors can capture the precise person’s area and rich information for the identification task as compared with popular RGB cameras. The authors apply four features extracted from images based on depth information to the identification method; (1) estimated body height, (2) estimated body dimensions, (3) estimated body size and (4) depth histogram. In the experiment, the authors evaluated two situations; (a) standing in front of a door and (b) touching a doorknob. The identification accuracy rates are 94.4% and 91.4% on the two situations. The authors obtained the high accuracy by the proposed method.

scholarly journals A Fast and Efficient Palmprint Identification Method for a Large Database

1970 ◽  
Vol 5 (2) ◽  
pp. 118-126 ◽  
Author(s):  
Mongkon Sakdanupab ◽  
Nongluk Covavisaruch
Keyword(s):  
Template Matching ◽  
Hamming Distance ◽  
Gabor Filter ◽  
Experimental Results ◽  
Large Database ◽  
Identification Methods ◽  
Palmprint Identification ◽  
Identification Method ◽  
Head Line ◽  
Log Gabor

This paper proposes a fast and efficient palmprint identification method for a large database. The process is accelerated as a result of our efficient palmprint classification and matching scheme. Palmprint classification method is based on principle lines which are life line, head line and heart line. Palmprints’ features are extracted with Log-Gabor filter and matched with Hamming distance in the most potential palmprint group/category, and if necessary, continues orderly to the less potential ones. Experiments are done with 2 hand databases, Visgraph database and CU-CGCI hand database. Experimental results show that the proposed method can greatly reduce the number of template matching from 100% (as in general identification methods) to 33.2-38.2% while maintaining the equivalent EER as the general identification method.

Real-Time Identification and Tracking of Infrared Markers Based on Kalman Filter

2012 ◽  
Vol 249-250 ◽  
pp. 1147-1153
Author(s):  
Qiao Na Xing ◽  
Da Yuan Yan ◽  
Xiao Ming Hu ◽  
Jun Qin Lin ◽  
Bo Yang
Keyword(s):  
Kalman Filter ◽  
Visible Light ◽  
Real Time ◽  
Complex Terrain ◽  
Experimental Results ◽  
Identification Method ◽  
In The Wild ◽  
Real Time Identification

Automatic equipmenttransportation in the wild complex terrain circumstances is very important in rescue or military. In this paper, an accompanying system based on the identification and tracking of infrared LEDmarkers is proposed. This system avoidsthe defect that visible-light identification method has. In addition, this paper presents a Kalman filter to predict where infraredmarkers may appear in the nextframe imageto reduce the searchingarea of infrared markers, which remarkablyimproves the identificationspeed of infrared markers. The experimental results show that the algorithm proposed in this paper is effective and feasible.

Analysis of Identification Methods of Key Nodes in Transportation Network

2022 ◽  
Author(s):  
Qiang Lai ◽  
Hong-hao Zhang
Keyword(s):  
Transportation Networks ◽  
Transportation Network ◽  
Practical Significance ◽  
Node Degree ◽  
Connected Subgraph ◽  
Network Efficiency ◽  
Identification Methods ◽  
Identification Method ◽  
Bus Networks ◽  
Key Nodes

Abstract The identification of key nodes plays an important role in improving the robustness of the transportation network. For different types of transportation networks, the effect of the same identification method may be different. It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks. Based on the knowledge of complex networks, the metro networks and the bus networks are selected as the objects, and the key nodes are identified by the node degree identification method, the neighbor node degree identification method, the weighted k-shell degree neighborhood identification method (KSD), the degree k-shell identification method (DKS), and the degree k-shell neighborhood identification method (DKSN). Take the network efficiency and the largest connected subgraph as the effective indicators. The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.

Experimental Robot Identification: Advantages of Combining Internal and External Measurements and of Using Periodic Excitation

2001 ◽  
Vol 123 (4) ◽  
pp. 630-636 ◽  
Author(s):  
Walter Verdonck ◽  
Jan Swevers ◽  
Jean-Claude Samin
Keyword(s):  
Signal Processing ◽  
Parameter Estimation ◽  
Effective Means ◽  
Base Plate ◽  
Experimental Results ◽  
Parameter Estimates ◽  
Periodic Excitation ◽  
Identification Method ◽  
Reaction Forces ◽  
Improved Model

This paper discusses the advantages of using periodic excitation and of combining internal and external measurements in experimental robot identification. This discussion is based on the robot identification method developed by Swevers et al., a method that is recognized by industry as an effective means of robot identification that is frequently used, Hirzinger, G., Fischer, M., Brunner, B., Koeppe, R., Otter, M., Grebenstein, M., and Schafer, I, 1999, “Advances is Robotics: The DLR Experiment,” The International Journal of Robotics Research, Vol. 18, No. 11, pp. 1064–1087 [3]. Experimental results on a KUKA IR 361 show that the periodicity of the robot excitation is a key element of this method. Nonperiodic robot excitation complicates the signal processing preceding the parameter estimation, often yielding less accurate parameter estimates. An extension of this identification method combines internal and external measurements, Chenut, X., Samin, J. C., Swevers, J., and Ganseman, C., 2000, “Combining Internal and External robot Models for improved Model Parameter Estimation,” Mechanical Systems and Signal Processing. Vol. 14, No. 5, pp. 691–704 [4], yielding robot models that allow to accurately predict the actuator torques and the reaction forces/torques of the robot on its base plate, which are both important for the path planning. This paper presents and critically discusses the first experimental results obtained with this method.

Face Recognition

2011 ◽  
pp. 163-254
Author(s):  
Daijin Kim ◽  
Jaewon Sung
Keyword(s):  
Face Recognition ◽  
Access Control ◽  
Individual Identification ◽  
Modern Life ◽  
Identification Methods ◽  
Personal Security ◽  
Identification Method ◽  
The Individual ◽  
Biometric Features

In the modern life, the need for personal security and access control is becoming an important issue. Biometrics is the technology which is expected to replace traditional authentication methods that are easily stolen, forgotten and duplicated. Fingerprints, face, iris, and voiceprints are commonly used biometric features. Among these features, face provides a more direct, friendly and convenient identification method and is more acceptable compared with the individual identification methods of other biometrics features. Thus, face recognition is one of the most important parts in biometrics.

scholarly journals A Parameter Identification Method for Stewart Manipulator Based on Wavelet Transform

Mathematics ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 257
Author(s):  
Chenyang Zhang
Keyword(s):  
Wavelet Transform ◽  
Parameter Identification ◽  
Coulomb Friction ◽  
Velocity Analysis ◽  
Dynamical Parameter ◽  
New Approach ◽  
Identification Methods ◽  
Identification Method ◽  
True Value ◽  
Joint Velocity

Aiming at inertial and viscous parameter identification for the Stewart manipulator regardless of the influence of Coulomb friction, a simple and effective dynamical parameter identification method based on wavelet transform and joint velocity analysis is proposed in this paper. Compared with previously known identification methods, the advantages of the new approach are that (1) the excitation trajectory is easy to design, and (2) it can not only identify the inertial matrix, but also the viscous matrix accurately regardless of the influence of Coulomb friction. Comparison is made among the identification method proposed in this paper, another identification method proposed previously, and the true value calculated with a formula. The errors from results of different identification methods demonstrate that the method proposed in this paper shows great adaptability and accuracy.

scholarly journals Optimization of virtual and real registration technology based on augmented reality in a surgical navigation system

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Long Chen ◽  
Fengfeng Zhang ◽  
Wei Zhan ◽  
Minfeng Gan ◽  
Lining Sun
Keyword(s):  
Augmented Reality ◽  
Navigation System ◽  
Surgical Navigation ◽  
Experimental Results ◽  
Lesion Area ◽  
Robot Assisted ◽  
Identification Method ◽  
Average Accuracy ◽  
True Shape ◽  
Navigation Interface

Abstract Background The traditional navigation interface was intended only for two-dimensional observation by doctors; thus, this interface does not display the total spatial information for the lesion area. Surgical navigation systems have become essential tools that enable for doctors to accurately and safely perform complex operations. The image navigation interface is separated from the operating area, and the doctor needs to switch the field of vision between the screen and the patient’s lesion area. In this paper, augmented reality (AR) technology was applied to spinal surgery to provide more intuitive information to surgeons. The accuracy of virtual and real registration was improved via research on AR technology. During the operation, the doctor could observe the AR image and the true shape of the internal spine through the skin. Methods To improve the accuracy of virtual and real registration, a virtual and real registration technique based on an improved identification method and robot-assisted method was proposed. The experimental method was optimized by using the improved identification method. X-ray images were used to verify the effectiveness of the puncture performed by the robot. Results The final experimental results show that the average accuracy of the virtual and real registration based on the general identification method was 9.73 ± 0.46 mm (range 8.90–10.23 mm). The average accuracy of the virtual and real registration based on the improved identification method was 3.54 ± 0.13 mm (range 3.36–3.73 mm). Compared with the virtual and real registration based on the general identification method, the accuracy was improved by approximately 65%. The highest accuracy of the virtual and real registration based on the robot-assisted method was 2.39 mm. The accuracy was improved by approximately 28.5% based on the improved identification method. Conclusion The experimental results show that the two optimized methods are highly very effective. The proposed AR navigation system has high accuracy and stability. This system may have value in future spinal surgeries.

Fast Face Detection Based on AdaBoost and Canny Operators

2014 ◽  
Vol 716-717 ◽  
pp. 936-939
Author(s):  
Lin Zhang
Keyword(s):  
Face Detection ◽  
Detection Method ◽  
Face Image ◽  
Experimental Results ◽  
Detection Accuracy ◽  
Human Face ◽  
Adaboost Algorithm ◽  
Amount Of Information ◽  
Detection Speed

Detection speed of traditional face detection method based on AdaBoost algorithm is slow since AdaBoost asks a large number of features. Therefore, to address this shortcoming, we proposed a fast face detection method based on AdaBoost and canny operators in this paper. Firstly, we use canny operators to detect edge of face image which separates the region of the possible human face from image, and then do face detection in the separated region using Modest AdaBoost algorithm (MAB). Before using MAB to achieve face detection, utilizing canny operators to detect edge can make this algorithm effectively filter information, retain useful information, reduce the amount of information and improve detection speed. Experimental results show that the algorithm can obtain higher detection accuracy and detection speed has been significantly improved at the same time.

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