View-Invariant Gait Recognition Based on Head and Shoulder Shape Analysis

2014 ◽  
Vol 568-570 ◽  
pp. 705-709
Author(s):  
Guo Zhen Wang ◽  
Hua Zhang ◽  
Li Jia Wang ◽  
Zhen Jie Wang
Keyword(s):  
Gait Analysis ◽  
Shape Analysis ◽  
Gait Cycle ◽  
Average Distance ◽  
Gait Recognition ◽  
Recognition Rate ◽  
Invariant Method ◽  
Discriminative Feature ◽  
Mean Shape ◽  
The Mean

To improve the recognition rate and resolve the view problem in gait analysis, a view-invariant method is presented. This method extracts the mean shape of the head and shoulder models in a gait cycle by using the Procrustes Shape Analysis (PSA) algorithm. Then, the mean shape is converted from 2-D space to 1-D space by unfolding the 2D mean shape from the top point of the head. Furthermore, the piecewise approximation (PA) of the unfolded mean shape is segmented corresponding to the average distance value. The obtained PA is adopted for estimating views and recognizing the gait. Finally, the presented method is conducted on the CASIA B database. The results illustrate that the PA is a powerful discriminative feature for view estimation and gait recognition, and the performance has been improved when there is view variation.

The Research on Shape Context Based on Gait Sequence Image

2018 ◽  
Vol 9 (2) ◽  
pp. 21-35
Author(s):  
Rong Wang ◽  
Yongkang Liu ◽  
Mengnan Hu
Keyword(s):  
Minimum Distance ◽  
Gait Cycle ◽  
Gait Recognition ◽  
Recognition Rate ◽  
Polar Coordinates ◽  
Target Area ◽  
Shape Context ◽  
Feature Extraction Method ◽  
Sampling Points ◽  
Gait Feature

A gait feature extraction method based on resampling shape context is proposed in this article. First, the moving target detection is carried out to obtain the target area of the human body. Second, the gait cycle is measured, and the contour points and the lower limb joints are selected as sampling points. Then, the different sampling points is placed in the polar coordinates of the origin, the number of sampling points in different cells is counted as the shape context; Finally, the feature vectors are constructed according to the shape context, and the minimum distance is used for classification and recognition. Simulation experiments based on resampling shape context are tested in CASIA gait Database A and Database B. The experimental results show that the method proposed in this article has a lower computational complexity and higher recognition rate when compared with the original shape context method, which can be used for gait recognition.

scholarly journals Gait Recognition of Acceleration Sensor for Smart Phone Based on Multiple Classifier Fusion

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Zhan Huan ◽  
Xuejie Chen ◽  
Shiyun Lv ◽  
Hongyang Geng
Keyword(s):  
Gait Cycle ◽  
Linear Time ◽  
Gait Recognition ◽  
Recognition Rate ◽  
Classifier Fusion ◽  
Velocity Change ◽  
Multiple Classifiers ◽  
Acceleration Sensors ◽  
Gait Features ◽  
New Feature

Gait, as a kind of biological feature, has a profound value in personnel identification. This paper analyzes gait characteristics based on acceleration sensors of smart phones and proposes a new gait recognition method. First, in view of the existing methods in the process of extraction of gait features, a large number of redundant calculations, cycle detection error, and the phase deviation issue during the week put forward the Shape Context (SC) and Linear Time Normalized (LTN) combining SCLTN calibration method of gait cycle sequence matching, to represent the whole extract typical gait cycle gait. In view of the existing extracted gait features are still some conventional features; the velocity change of relatively uniform acceleration and the change of acceleration per unit time are proposed as new features. Secondly, combining new features with traditional features to form a new feature is set for training alternative feature set, from which the training time and recognition effect of multiple classifiers are screened. Finally, a new multiclassifier fusion method, Multiple Scale Voting (MSV), is proposed to fuse the results of Multiple classifiers to obtain the final classification results. In order to verify the performance of the proposed method, gait data of 32 testers are collected. The final experimental results show that the new feature has good separability, and the recognition rate of fusion feature set after MSV algorithm is 98.42%.

scholarly journals Image Enhanced Mask R-CNN: A Deep Learning Pipeline with New Evaluation Measures for Wind Turbine Blade Defect Detection and Classification

2021 ◽  
Vol 7 (3) ◽  
pp. 46
Author(s):  
Jiajun Zhang ◽  
Georgina Cosma ◽  
Jason Watkins
Keyword(s):  
Deep Learning ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Defect Detection ◽  
Recognition Rate ◽  
Weighted Average ◽  
Wind Turbine Blade ◽  
Evaluation Measures ◽  
Augmentation Techniques ◽  
The Mean

Demand for wind power has grown, and this has increased wind turbine blade (WTB) inspections and defect repairs. This paper empirically investigates the performance of state-of-the-art deep learning algorithms, namely, YOLOv3, YOLOv4, and Mask R-CNN for detecting and classifying defects by type. The paper proposes new performance evaluation measures suitable for defect detection tasks, and these are: Prediction Box Accuracy, Recognition Rate, and False Label Rate. Experiments were carried out using a dataset, provided by the industrial partner, that contains images from WTB inspections. Three variations of the dataset were constructed using different image augmentation settings. Results of the experiments revealed that on average, across all proposed evaluation measures, Mask R-CNN outperformed all other algorithms when transformation-based augmentations (i.e., rotation and flipping) were applied. In particular, when using the best dataset, the mean Weighted Average (mWA) values (i.e., mWA is the average of the proposed measures) achieved were: Mask R-CNN: 86.74%, YOLOv3: 70.08%, and YOLOv4: 78.28%. The paper also proposes a new defect detection pipeline, called Image Enhanced Mask R-CNN (IE Mask R-CNN), that includes the best combination of image enhancement and augmentation techniques for pre-processing the dataset, and a Mask R-CNN model tuned for the task of WTB defect detection and classification.

scholarly journals Multimodal Low Resolution Face and Frontal Gait Recognition from Surveillance Video

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1013
Author(s):  
Sayan Maity ◽  
Mohamed Abdel-Mottaleb ◽  
Shihab S. Asfour
Keyword(s):  
Face Recognition ◽  
High Resolution ◽  
Gait Cycle ◽  
Gait Recognition ◽  
Recognition System ◽  
Multimodal Fusion ◽  
Surveillance Video ◽  
Low Resolution ◽  
Model Free ◽  
Face Images

Biometric identification using surveillance video has attracted the attention of many researchers as it can be applicable not only for robust identification but also personalized activity monitoring. In this paper, we present a novel multimodal recognition system that extracts frontal gait and low-resolution face images from frontal walking surveillance video clips to perform efficient biometric recognition. The proposed study addresses two important issues in surveillance video that did not receive appropriate attention in the past. First, it consolidates the model-free and model-based gait feature extraction approaches to perform robust gait recognition only using the frontal view. Second, it uses a low-resolution face recognition approach which can be trained and tested using low-resolution face information. This eliminates the need for obtaining high-resolution face images to create the gallery, which is required in the majority of low-resolution face recognition techniques. Moreover, the classification accuracy on high-resolution face images is considerably higher. Previous studies on frontal gait recognition incorporate assumptions to approximate the average gait cycle. However, we quantify the gait cycle precisely for each subject using only the frontal gait information. The approaches available in the literature use the high resolution images obtained in a controlled environment to train the recognition system. However, in our proposed system we train the recognition algorithm using the low-resolution face images captured in the unconstrained environment. The proposed system has two components, one is responsible for performing frontal gait recognition and one is responsible for low-resolution face recognition. Later, score level fusion is performed to fuse the results of the frontal gait recognition and the low-resolution face recognition. Experiments conducted on the Face and Ocular Challenge Series (FOCS) dataset resulted in a 93.5% Rank-1 for frontal gait recognition and 82.92% Rank-1 for low-resolution face recognition, respectively. The score level multimodal fusion resulted in 95.9% Rank-1 recognition, which demonstrates the superiority and robustness of the proposed approach.

scholarly journals A cadaveric study of the location and morphology of the central patellar ridge for bone-patellar tendon-bone graft

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Thanathep Tanpowpong ◽  
Thun Itthipanichpong ◽  
Thanasil Huanmanop ◽  
Nonn Jaruthien ◽  
Nattapat Tangchitcharoen
Keyword(s):  
Patellar Tendon ◽  
Cancellous Bone ◽  
Average Distance ◽  
Cadaveric Study ◽  
Anterior Cortex ◽  
Length Width ◽  
Central Ridge ◽  
The Mean ◽  
Bone Patellar Tendon ◽  
And Cartilage

Abstract Introduction The central ridge of the patella is the thickest area of patella and varies among patients. This cadaveric study identified the location and thickness of the bone at the central patella ridge for bone-patellar tendon-bone (BPTB) harvesting. Materials and methods Fifty cadaveric knees were assessed. First, the morphology, length, width, and location of the central patellar ridge were recorded. Then, we transversely cut the patella 25 mm from the lower pole and measured the thickness of the anterior cortex, cancellous bone, and cartilage from both the mid-patella and the central ridge location. Finally, the depth of the remaining cancellous bone at the mid-patella was compared to the bone at the central ridge. Results The location of the central-patellar ridge deviated medially from the mid-patella in 46 samples with an average distance of 4.36 ± 1 mm. Only 4 samples deviated laterally. The mean patella length was 41.19 ± 4.73 mm, and the width was 42.8 ± 5.25 mm. After a transverse cut, the remaining cancellous bone was significantly thicker at the central ridge compared to the bone at the mid-patella. Conclusions Most of the central patellar ridge deviated medially, approximately 4 mm from the mid-patella. Harvesting the graft from the central ridge would have more remaining bone compared to the mid-patella.

Design of Gait Recognition System Based on FPGA and DSP

2014 ◽  
Vol 687-691 ◽  
pp. 3861-3868
Author(s):  
Zheng Hong Deng ◽  
Li Tao Jiao ◽  
Li Yan Liu ◽  
Shan Shan Zhao
Keyword(s):  
Monitoring System ◽  
Nearest Neighbor ◽  
Gait Recognition ◽  
Recognition Rate ◽  
Digital Signal ◽  
Recognition System ◽  
Recognition Algorithm ◽  
Zernike Moment ◽  
Intelligent Monitoring ◽  
The One

According to the trend of the intelligent monitoring system, on the basis of the study of gait recognition algorithm, the intelligent monitoring system is designed based on FPGA and DSP; On the one hand, FPGA’s flexibility and fast parallel processing algorithms when designing can be both used to avoid that circuit can not be modified after designed; On the other hand, the advantage of processing the digital signal of DSP is fully taken. In the feature extraction and recognition, Zernike moment is selected, at the same time the system uses the nearest neighbor classification method which is more mature and has good real-time performance. Experiments show that the system has high recognition rate.

The Mean Shape of the Human Cornea

1982 ◽  
Vol 29 (8) ◽  
pp. 1027-1040 ◽  
Author(s):  
P.M. Kiely ◽  
G. Smith ◽  
L.G. Carney
Keyword(s):  
Human Cornea ◽  
Mean Shape ◽  
The Mean

scholarly journals Evaluation of a treadmill with integrated force plates for kinetic gait analysis of sound and lame dogs at a trot

2006 ◽  
Vol 19 (04) ◽  
pp. 205-212 ◽  
Author(s):  
N. M. M. Moens ◽  
J. R. Runciman ◽  
N. S. Brebner
Keyword(s):  
Gait Analysis ◽  
Correlation Coefficients ◽  
Force Platform ◽  
Target Velocity ◽  
Vertical Force ◽  
Belt Speed ◽  
Hind Limbs ◽  
The Mean ◽  
Good Concordance

SummaryThe objective was to compare mean peak vertical force (PVF) obtained with a treadmill with two integrated force plates (TM) with the piezoelectric force platform (FP) for sound and lame dogs at a trot. The aim was also to report the inter-step variability (ISV) for both systems and the effect of lameness on these values. Six sound dogs (20.0–25.5 kg) and six dogs with a grade 2/5 forelimb lameness (17.0–36.1 kg) were used in the study. Dogs were acclimatized and assigned an individual target velocity (1.8–2.2 m/s). Mean PVF measurements were obtained for both TM and FP. Subject velocity was controlled by belt speed on TM and restricted to 0.25 M/s above or below the assigned target velocity for FP. Acceleration was limited to +/- 0.3 M/s2. For the sound dogs, concordance and correlation coefficients of the mean PVF for the front limbs was 0.79 and 0.76, respectively. Concordance and correlation for the rear limbs was 0.90 and 0.81, respectively. For the lame dogs, concordance and correlation for the front limbs was 0.73 and 0.59, respectively. Concordance and correlation for the rear limbs was 0.89 and 0.95, respectively. ISV was 0.94 with TM and 0.84 with FP for the sound dogs and 0.96 with TM and 0.87 with FP for the lame dogs. In conclusion, TM provided rapid PVF measurements, good concordance for the hind limbs, and substantial concordance for the forelimbs in both sound and lame dogs at a trot as compared to FP. Both systems demonstrated excellent ISV for both lame and sound dogs.

scholarly journals Gait Analysis Using Accelerometry Data from a Single Smartphone: Agreement and Consistency between a Smartphone Application and Gold-Standard Gait Analysis System

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7497
Author(s):  
Roy T. Shahar ◽  
Maayan Agmon
Keyword(s):  
Gait Analysis ◽  
Gold Standard ◽  
Concurrent Validity ◽  
Gait Cycle ◽  
Intraclass Correlation ◽  
Smartphone Application ◽  
Healthy Adults ◽  
Community Dwelling ◽  
Human Gait ◽  
Spatio Temporal

Spatio-temporal parameters of human gait, currently measured using different methods, provide valuable information on health. Inertial Measurement Units (IMUs) are one such method of gait analysis, with smartphone IMUs serving as a good substitute for current gold-standard techniques. Here we investigate the concurrent validity of a smartphone placed in a front-facing pocket to perform gait analysis. Sixty community-dwelling healthy adults equipped with a smartphone and an application for gait analysis completed a 2-min walk on a marked path. Concurrent validity was assessed against an APDM mobility lab (APDM Inc.; Portland, OR, USA). Bland–Altman plots and intraclass correlation coefficients (agreement and consistency) for gait speed, cadence, and step length indicate good to excellent agreement (ICC2,1 > 0.8). For right leg stance and swing % of gait cycle and double support % of gait cycle, results were moderate (0.52 < ICC2,1 < 0.62). For left leg stance and swing % of gait cycle left results show poor agreement (ICC2,1 < 0.5). Consistency of results was good to excellent for all tested parameters (ICC3,1 > 0.8). Thus we have a valid and reliable instrument for measuring healthy adults’ spatio-temporal gait parameters in a controlled walking environment.

scholarly journals Surgical and Postoperative Evaluations of Rectal Adenomas Ecised With a Novel Proctoscope.

2020 ◽  
Author(s):  
Roberta Denise Alkmin Lopes Lima ◽  
Rogerio Serafim Parra ◽  
Marley Ribeiro Feitosa ◽  
Omar Féres ◽  
José Joaquim Ribeiro Rocha
Keyword(s):  
Operative Time ◽  
Average Distance ◽  
Economic Feasibility ◽  
Surgeon Experience ◽  
Average Operative Time ◽  
The Mean ◽  
Average Size ◽  
High Level ◽  
Complex Methods

Abstract Purpose Many transanal endoscopic surgeries require a high level of technical expertise and surgeon experience. Considering the economic feasibility of material acquisition and the technical feasibility of training and experience with complex methods, a simpler technique with available resources is relevant for the excision of rectal adenomas. This study presents the surgical and postoperative results achieved with a novel proctoscope using the transanal endoscopic technique to excise rectal adenomas. The results are compared to the results obtained with other currently employed transanal techniques. Methods We retrospectively investigated the medical records of patients who underwent transanal endoscopic operations from April 2000 to June 2018 at two tertiary referral centers for colorectal cancer. Results This study included 99 patients. The mean age was 65.3 ± 13.3 years. The average size of the adenomas was 4.6 ± 2.3 cm, and their average distance to the anal border was 5.6 ± 3.3 cm. The average operative time was 65.3 ± 41.7 min. In 48.5% of the operations, the specimen was fragmented, and in 59.6% of the cases, the microscopic margins were free. The rates of postoperative complications and relapse were 5% and 19%, respectively. The mean follow-up was 80 ± 61.5 months. Conclusions The described proctoscope proved to be a viable technique with results similar to other techniques, with the advantage that it allowed greater accessibility for surgeons. Therefore, its use could be implemented and become widespread in surgical practice.

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