scholarly journals Performance Evaluation of rPPG Approaches with and without the Region-of-Interest Localization Step

2021 ◽  
Vol 11 (8) ◽  
pp. 3467
Author(s):  
Žan Pirnar ◽  
Miha Finžgar ◽  
Primož Podržaj
Keyword(s):  
Skin Color ◽  
Region Of Interest ◽  
Signal Extraction ◽  
Color Segmentation ◽  
Data Sets ◽  
Success Rates ◽  
Model Based ◽  
Video Recordings ◽  
Lighting Conditions ◽  
Maximization Of Mutual Information

Traditionally, the first step in physiological measurements based on remote photoplethysmography (rPPG) is localizing the region of interest (ROI) that contains a desired pulsatile information. Recently, approaches that do not require this step have been proposed. The purpose of this study was to evaluate the performance of selected approaches with and without ROI localization step in rPPG signal extraction. The Viola-Jones face detector and Kanade–Lucas–Tomasi tracker (VK) in combination with (a) a region-of-interest (ROI) cropping, (b) facial landmarks, (c) skin-color segmentation, and (d) skin detection based on maximization of mutual information and an approach without ROI localization step (Full Video Pulse (FVP)) were studied. Final rPPG signals were extracted using selected model-based and data-driven rPPG algorithms. The performance of the approaches was tested on three publicly available data sets offering compressed and uncompressed video recordings covering various scenarios. The success rates of pulse waveform signal extraction range from 88.37% (VK with skin-color segmentation) to 100% (FVP). In challenging scenarios (skin tone, lighting conditions, exercise), there were no statistically significant differences between the studied approaches in terms of SNR. The best overall performance in terms of RMSE was achieved by a combination of VK with ROI cropping and the model-based rPPG algorithm. Results indicate that the selection of the ROI localization approach does not significantly affect rPPG measurements if combined with a robust algorithm for rPPG signal extraction.

scholarly journals Predicting Damage to Hop Cones by Tetranychus urticae (Acari: Tetranychidae)

2021 ◽  
Author(s):  
Joanna L Woods ◽  
Anne E Iskra ◽  
David H Gent
Keyword(s):  
Risk Factors ◽  
Tetranychus Urticae ◽  
Crop Damage ◽  
Equation Modeling ◽  
Data Sets ◽  
Current Management ◽  
Late Season ◽  
Model Based ◽  
Predatory Arthropods ◽  
Cone Damage

Abstract Twospotted spider mite (Tetranychus urticae Koch) is a cosmopolitan pest of numerous plants, including hop (Humulus lupulus L.). The most costly damage from the pest on hop results from infestation of cones, which are the harvested product, which can render crops unsalable if cones become discolored. We analyzed 14 yr of historical data from 312 individual experimental plots in western Oregon to identify risk factors associated with visual damage to hop cones from T. urticae. Logistic regression models were fit to estimate the probability of cone damage. The most predictive model was based on T. urticae-days during mid-July to harvest, which correctly predicted occurrence and nonoccurrence of cone damage in 91 and 93% of data sets, respectively, based on Youden’s index. A second model based on the ratio of T. urticae to predatory arthropods late in the season correctly predicted cone damage in 92% of data sets and nonoccurrence of damage in 77% of data sets. The model based on T. urticae abundance performed similarly when validated in 23 commercial hop yards, whereas the model based on the predator:prey ratio was relatively conservative and yielded false-positive predictions in 11 of the 23 yards. Antecedents of these risk factors were explored and quantified by structural equation modeling. A simple path diagram was constructed that conceptualizes T. urticae invasion of hop cones as dependent on prior density of the pest on leaves in early spring and summer, which in turn influences the development of predatory arthropods that mediate late-season density of the pest. In summary, the biological insights and models developed here provide guidance to pest managers on the likelihood of visual cone damage from T. urticae that can inform late-season management based on both abundance of the pest and its important predators. This is critically important because a formal economic threshold for T. urticae on hop does not exist and current management efforts may be mistimed to influence the pest when crop damage is most probable. More broadly, this research suggests that current management practices that target T. urticae early in the season may in fact predispose yards to later outbreaks of the pest.

The Player Load Associated With Typical Activities in Elite Netball

2017 ◽  
Vol 12 (9) ◽  
pp. 1218-1223 ◽  
Author(s):  
Jared A. Bailey ◽  
Paul B. Gastin ◽  
Luke Mackey ◽  
Dan B. Dwyer
Keyword(s):  
Training Programs ◽  
Data Sets ◽  
Specific Training ◽  
Start Time ◽  
Total Load ◽  
Future Design ◽  
Design And Implementation ◽  
Video Recordings ◽  
Wearable Accelerometers

Context:Most previous investigations of player load in netball have used subjective methodologies, with few using objective methodologies. While all studies report differences in player activities or total load between playing positions, it is unclear how the differences in player activity explain differences in positional load. Purpose:To objectively quantify the load associated with typical activities for all positions in elite netball. Methods:The player load of all playing positions in an elite netball team was measured during matches using wearable accelerometers. Video recordings of the matches were also analyzed to record the start time and duration of 13 commonly reported netball activities. The load associated with each activity was determined by time-aligning both data sets (load and activity). Results:Off-ball guarding produced the highest player load per instance, while jogging produced the greatest player load per match. Nonlocomotor activities contributed least to total match load for attacking positions (goal shooter [GS], goal attack [GA], and wing attack [WA]) and most for defending positions (goalkeeper [GK], goal defense [GD], and wing defense [WD]). Specifically, centers (Cs) produced the greatest jogging load, WA and WD accumulated the greatest running load, and GS and WA accumulated the greatest shuffling load. WD and Cs accumulated the greatest guarding load, while WD and GK accumulated the greatest off-ball guarding load. Conclusions:All positions exhibited different contributions from locomotor and nonlocomotor activities toward total match load. In addition, the same activity can have different contributions toward total match load, depending on the position. This has implications for future design and implementation of position-specific training programs.

A Novel Approach of Face Detection Based on Skin Color Segmentation and SVM

2011 ◽  
Vol 225-226 ◽  
pp. 437-441
Author(s):  
Jing Zhang ◽  
You Li
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Information Access ◽  
Color Segmentation ◽  
Support Vector ◽  
Svm Classifier ◽  
Novel Approach ◽  
Great Performance ◽  
Face Detection And Recognition ◽  
Detection And Recognition

Nowadays, face detection and recognition have gained importance in security and information access. In this paper, an efficient method of face detection based on skin color segmentation and Support Vector Machine(SVM) is proposed. Firstly, segmenting image using color model to filter candidate faces roughly; And then Eye-analogue segments at a given scale are discovered by finding regions which are darker than their neighborhoods to filter candidate faces farther; at the end, SVM classifier is used to detect face feature in the test image, SVM has great performance in classification task. Our tests in this paper are based on MIT face database. The experimental results demonstrate that the proposed method is encouraging with a successful detection rate.

QSAR model based on weighted MCS trees approach for the representation of molecule data sets

2013 ◽  
Vol 27 (2) ◽  
pp. 185-201 ◽  
Author(s):  
Bernardo Palacios-Bejarano ◽  
Gonzalo Cerruela García ◽  
Irene Luque Ruiz ◽  
Miguel Ángel Gómez-Nieto
Keyword(s):  
Qsar Model ◽  
Data Sets ◽  
Model Based

Lighting Equilibrium Distribution Maps and Their Application to Face Recognition Under Difficult Lighting Conditions

2017 ◽  
Vol 31 (03) ◽  
pp. 1756003 ◽  
Author(s):  
Jun Dong ◽  
Xue Yuan ◽  
Fanlun Xiong
Keyword(s):  
Face Recognition ◽  
Equilibrium Distribution ◽  
Main Idea ◽  
Data Sets ◽  
Test Image ◽  
Distribution Maps ◽  
Lighting Conditions ◽  
Map Construction ◽  
Compensation Methods ◽  
Approximation Coefficients

In this paper, a novel facial-patch based recognition framework is proposed to deal with the problem of face recognition (FR) on the serious illumination condition. First, a novel lighting equilibrium distribution maps (LEDM) for illumination normalization is proposed. In LEDM, an image is analyzed in logarithm domain with wavelet transform, and the approximation coefficients of the image are mapped according to a reference-illumination map in order to normalize the distribution of illumination energy due to different lighting effects. Meanwhile, the detail coefficients are enhanced to achieve detail information emphasis. The LEDM is obtained by blurring the distances between the test image and the reference illumination map in the logarithm domain, which may express the entire distribution of illumination variations. Then, a facial-patch based framework and a credit degree based facial patches synthesizing algorithm are proposed. Each normalized face images is divided into several stacked patches. And, all patches are individually classified, then each patch from the test image casts a vote toward the parent image classification. A novel credit degree map is established based on the LEDM, which is deciding a credit degree for each facial patch. The main idea of credit degree map construction is the over-and under-illuminated regions should be assigned lower credit degree than well-illuminated regions. Finally, results are obtained by the credit degree based facial patches synthesizing. The proposed method provides state-of-the-art performance on three data sets that are widely used for testing FR under different illumination conditions: Extended Yale-B, CAS-PEAL-R1, and CMUPIE. Experimental results show that our FR frame outperforms several existing illumination compensation methods.

Elastic model-based segmentation of 3-D neuroradiological data sets

1999 ◽  
Vol 18 (10) ◽  
pp. 828-839 ◽  
Author(s):  
A. Kelemen ◽  
G. Szekely ◽  
G. Gerig
Keyword(s):  
Elastic Model ◽  
Data Sets ◽  
Model Based

scholarly journals An Innovative Face Detection Based on YCgCr Color Space

2018 ◽  
Author(s):  
Solly Aryza
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Color Image ◽  
Color Space ◽  
Gaussian Model ◽  
Detection Rates ◽  
Detection Algorithms ◽  
Lighting Conditions ◽  
Wide Range ◽  
Human Faces

It is very challenging to recognize a face from an image due to the wide variety of face and the uncertain of face position. The research on detecting human faces in color image and in video sequence has been attracted with more and more people. In this paper, we propose a novel face detection method that achieves better detection rates. The new face detection algorithms based on skin color model in YCgCr chrominance space. Firstly, we build a skin Gaussian model in Cg-Cr color space. Secondly, a calculation of correlation coefficient is performed between the given template and the candidates. Experimental results demonstrate that our system has achieved high detection rates and low false positives over a wide range of facial variations in color, position and varying lighting conditions.

Sign in / Sign up

Export Citation Format

Share Document