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- Associate Professor Wanqing Li (9)
- Professor Philip Ogunbona (8)
- Adam Trevitt (5)
- Professor Salim Bouzerdoum (5)
- Gordon Wallace (3)
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- Cher Hau Seng (2)
- Dr Lei Wang (2)
- Robert Gorkin III (2)
- Stephen Blanksby (2)
- Tyler Harms (2)
- Associate Professor Golshah Naghdy (1)
- Associate Professor Kashem Muttaqi (1)
- Associate Professor Minjie Zhang (1)
- Associate Professor Sarath Perera (1)
- Dr Ahmed Mohamed Ahmed Haidar (1)
- Dr Fok Hing Chi Tivive (1)
- Dr Yanguang Yu (1)
- Heath Ecroyd (1)
- Jeremy Straub (1)
- Professor Fazel Naghdy (1)
- Professor Nick E Dixon (1)
- Professor Noel Cressie (1)
- Professor Pascal Perez (1)
- Sharon Robinson (1)
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Articles 1 - 30 of 54
Full-Text Articles in Physical Sciences and Mathematics
Influence Of Season And Time Of Day On Marsh Bird Detections, Tyler Harms, Stephen Dinsmore
Influence Of Season And Time Of Day On Marsh Bird Detections, Tyler Harms, Stephen Dinsmore
Tyler Harms
Call-broadcast surveys are frequently used to elicit responses of secretive marsh birds and produce greater detection rates than passive surveys. However, little is known about how detection rates of birds from these surveys differ by season and time of day. We conducted call-broadcast surveys for eight focal species at 56 wetlands throughout Iowa from 15 May–13 June 2010 (early season) and from 15 June–10 July 2010 (late season). Our focal species were Pied-billed Grebe (Podilymbus podiceps), American Bittern (Botaurus lentiginosus), Least Bittern (Ixobrychus exilis), King Rail (Rallus elegans), Virginia Rail (Rallus …
Influence Of Season And Time Of Day On Marsh Bird Detections, Tyler Harms, Stephen J. Dinsmore
Influence Of Season And Time Of Day On Marsh Bird Detections, Tyler Harms, Stephen J. Dinsmore
Tyler Harms
Call-broadcast surveys are frequently used to elicit responses of secretive marsh birds and produce greater detection rates than passive surveys. However, little is known about how detection rates of birds from these surveys differ by season and time of day. We conducted call-broadcast surveys for eight focal species at 56 wetlands throughout Iowa from 15 May–13 June 2010 (early season) and from 15 June–10 July 2010 (late season). Our focal species were Pied-billed Grebe (Podilymbus podiceps), American Bittern (Botaurus lentiginosus), Least Bittern (Ixobrychus exilis), King Rail (Rallus elegans), Virginia Rail (Rallus …
Design And Fabrication Of A Cop-Based Microfluidic Chip: Chronoamperometric Detection Of Troponin T, Llibertat Abad, Francisco Javier Del Campo, Francesc Xavier Munoz, Luis J Fernandez, Daniel Calavia, Gloria Colom, Juan P Salvador, Maria Pilar Marco, Vanessa Escamilla-Gomez, Berta Esteban-Fernandez De Avila, Susana Campuzano, Maria Pedrero, Jose M Pingarron, Neus Godino, Robert Gorkin Iii, Jens Ducree
Design And Fabrication Of A Cop-Based Microfluidic Chip: Chronoamperometric Detection Of Troponin T, Llibertat Abad, Francisco Javier Del Campo, Francesc Xavier Munoz, Luis J Fernandez, Daniel Calavia, Gloria Colom, Juan P Salvador, Maria Pilar Marco, Vanessa Escamilla-Gomez, Berta Esteban-Fernandez De Avila, Susana Campuzano, Maria Pedrero, Jose M Pingarron, Neus Godino, Robert Gorkin Iii, Jens Ducree
Robert Gorkin III
This work demonstrates the design and fabrication of an all cyclo-olefin polymer based microfluidic device capable of capturing magnetic beads and performing electrochemical detection in a series of gold electrodes. The size of chip is of a microscope slide and features six independent measuring cells formultianalyte detection purposes. The aim of this work is to show that rapid prototyping techniques can be instrumental in the development of novel bioassays, particularly in clinical diagnosis applications. We show the successful determination of troponin-T, a cardiac disease marker, in the clinically relevant range of 0.05–1.0 ng/mL. This methodology achieves a detection limit of …
Fabricating Electrodes For Amperometric Detection In Hybrid Paper/Polymer Lab-On-A-Chip Devices, Neus Godino, Robert Gorkin Iii, Ken Bourke, Jens Ducree
Fabricating Electrodes For Amperometric Detection In Hybrid Paper/Polymer Lab-On-A-Chip Devices, Neus Godino, Robert Gorkin Iii, Ken Bourke, Jens Ducree
Robert Gorkin III
We present a novel, low-resource fabrication and assembly method for creating disposable amperometric detectors in hybrid paper-polymer devices. Currently, mere paper-based microfluidics is far from being able to achieve the same level of process control and integration as state-of-the-art microfluidic devices made of polymers. To overcome this limitation, in this work both substrate types are synergistically combined through a hybrid, multi-component/multi-material system assembly. Using established inkjet wax printing, we transform the paper into a profoundly hydrophobic substrate in order to create carbon electrodes which are simply patterned from carbon inks via custom made adhesive stencils. By virtue of the compressibility …
Pattern Recognition For Detecting Failures In Space Solar Power Systems, Allen Mcdermott, Cameron Kerbaugh, Jeremy Straub, Eunjin Kim
Pattern Recognition For Detecting Failures In Space Solar Power Systems, Allen Mcdermott, Cameron Kerbaugh, Jeremy Straub, Eunjin Kim
Jeremy Straub
This poster covers work relating to the use of expert systems and pattern recognition to attempt to identify, detect and prospectively stop patterns of activity that could potentially lead to failure of a space solar power (SSP) system. A database-based expert system has is presented to identify patterns, which can be used to determine whether a power beam could hit a unintend- ed target and potentially cause a calamity. This has been implemented via a facts-rule network via which supplied and collected facts and a rule set is used to de- termine whether the system is operating correctly (from a …
Isomer-Specific Product Detection Of Cn Radical Reactions With Ethene And Propene By Tunable Vuv Photoionization Mass Spectrometry, Adam Trevitt, Fabien Goulay, Giovanni Meloni, David Osborn, Craig Taatjes, Stephen Leone
Isomer-Specific Product Detection Of Cn Radical Reactions With Ethene And Propene By Tunable Vuv Photoionization Mass Spectrometry, Adam Trevitt, Fabien Goulay, Giovanni Meloni, David Osborn, Craig Taatjes, Stephen Leone
Adam Trevitt
No abstract provided.
Pyrolysis Of Fulvenallene (C7h6) And Fulvenallenyl (C7h5): Theoretical Kinetics And Experimental Product Detection, Adam Trevitt, G Da Silva, M Steinbauer, P Hemberger
Pyrolysis Of Fulvenallene (C7h6) And Fulvenallenyl (C7h5): Theoretical Kinetics And Experimental Product Detection, Adam Trevitt, G Da Silva, M Steinbauer, P Hemberger
Adam Trevitt
Fulvenallene and fulvenallenyl are the respective C7H6 and C7H5 global minima, yet their importance to combustion has only recently emerged. We have studied the pyrolysis of these species theoretically to obtain rate constants and compare our results to pyrolysis mass spectrometry experiments for product identification. Master equation modeling reveals that fulvenallene rapidly dissociates to fulvenallenyl + H, and that fulvenallenyl dissociates to form propargyl plus diacetylene, with lesser amounts of i-C5H3 (CH2CCCCH)/n-C5H3 (CHCCHCCH) plus acetylene. Photoionization mass spectrometry experiments using a pyrolysis source on the fulvenallene precursor phthalide identify products consistent with those proposed theoretically for both fulvenallene and fulvenallenyl …
Reactions Of Small Carbon-Bearing Radicals With Unsaturated Hydrocarbons: Product Detection And Low Temperature Kinetics, Adam Trevitt, Fabien Goulay, Stephen Leone
Reactions Of Small Carbon-Bearing Radicals With Unsaturated Hydrocarbons: Product Detection And Low Temperature Kinetics, Adam Trevitt, Fabien Goulay, Stephen Leone
Adam Trevitt
We report on results from two experimental techniques concerned with the reactions of small carbon based radicals (CN and CH) with unsaturated hydrocarbons. First, low temperature (100-300K) kinetic studies using a pulse Laval nozzle technique probe the reactions of the CN radical with benzene and toluene. The CN + benzene is found to be a fast, barrierless reaction. But in the case of toluene, two reaction pathways are in competition, one of which back dissociates to the reactants. The implications for the atmosphere of Titan are discussed. Product detection studies undertaken at the Advanced Light Source (ALS) using synchrotron coupled …
Ultrasensitive Detection Of Antibodies Using A New Tus-Ter-Lock Immunopcr System, Isabelle Morin, Nicholas E. Dixon, Patrick M. Schaeffer
Ultrasensitive Detection Of Antibodies Using A New Tus-Ter-Lock Immunopcr System, Isabelle Morin, Nicholas E. Dixon, Patrick M. Schaeffer
Professor Nick E Dixon
A system consisting of a protein LG coated surface for the capture of mammalian antibodies (target), and an antigen fused to Tus and stoichiometrically linked to a DNA template via the Tus-Ter-lock sequence allowed the ultrasensitive detection of 5.5 attomol of target by real-time immunoPCR in complex media. © The Royal Society of Chemistry 2010.
Automatic Left Ventricle Detection In Echocardiographic Images For Deformable Contour Initialization, Cher Hau Seng, Ramazan Demirli, Moeness G. Amin, Jason L. Seachrist, Abdesselam Bouzerdoum
Automatic Left Ventricle Detection In Echocardiographic Images For Deformable Contour Initialization, Cher Hau Seng, Ramazan Demirli, Moeness G. Amin, Jason L. Seachrist, Abdesselam Bouzerdoum
Cher Hau Seng
The accurate left ventricular boundary detection in echocardiographic images allow cardiologists to study and assess cardiomyopathy in patients. Due to the tedious and time consuming manner of manually tracing the borders, deformable models are generally used for left ventricle segmentations. However, most deformable models require a good initialization, which is usually outlined manually by the user. In this paper, we propose an automated left ventricle detection method for two-dimensional echocardiographic images that could serve as an initialization for deformable models. The proposed approach consists of pre-processing and post-processing stages, coupled with the watershed segmentation. The pre-processing stage enhances the overall …
Seizure Detection In Eeg Signals Using Support Vector Machines, Cher Hau Seng, Ramazan Demirli, Lunal Khuon, Donovan Bolger
Seizure Detection In Eeg Signals Using Support Vector Machines, Cher Hau Seng, Ramazan Demirli, Lunal Khuon, Donovan Bolger
Cher Hau Seng
A linear Support Vector Machine (SVM) classifier is designed to detect and classify seizures in EEG signals based on a few simple features such as mean, variance, dominant frequency, and the mean power spectrum. The SVM classifier is tested on a benchmark EEG database. Using a combination of these features, classification rates up to 98% were achieved. The proposed classifier that utilizes a few simple features is computationally efficient to be deployed in a real-time seizure monitoring system.
Fabrication Of Polyaniline-Based Gas Sensors Using Piezoelectric Inkjet And Screen Printing For The Detection Of Hydrogen Sulfide, Karl H. Crowley, Aoife Morrin, Roderick L. Shepherd, Marc In Het Panhuis, Gordon G. Wallace, Malcolm R. Smyth, Anthony J. Killard
Fabrication Of Polyaniline-Based Gas Sensors Using Piezoelectric Inkjet And Screen Printing For The Detection Of Hydrogen Sulfide, Karl H. Crowley, Aoife Morrin, Roderick L. Shepherd, Marc In Het Panhuis, Gordon G. Wallace, Malcolm R. Smyth, Anthony J. Killard
Gordon Wallace
This work describes a fully printable polyaniline-copper (II) chloride sensor for the detection of hydrogen sulfide gas. The sensing device is composed of screen printed silver interdigitated electrode (IDE) on a flexible PET substrate with inkjet printed layers of polyaniline and copper (II) chloride. The sensor is employed as a chemiresistor with changes in measured current being correlated with concentration. On exposure to hydrogen sulfide, 2.5 ppmv (parts per million by volume) is clearly detectable with a linear relationship between measured current and concentration over the 10-100 ppmv region. The detection mechanism is discussed with respect to the hydrogen sulfide …
Fabrication Of Chemical Sensors Using Inkjet Printing And Application To Gas Detection, Karl H. Crowley, Aoife Morrin, Malcolm R. Smyth, Anthony J. Killard, Roderick Shepherd, Marc In Het Panhuis, Gordon G. Wallace
Fabrication Of Chemical Sensors Using Inkjet Printing And Application To Gas Detection, Karl H. Crowley, Aoife Morrin, Malcolm R. Smyth, Anthony J. Killard, Roderick Shepherd, Marc In Het Panhuis, Gordon G. Wallace
Gordon Wallace
This work describes the fabrication of gas sensors using inkjet printing. Sensors were constructed by building up a film of sensing material, such as polyaniline, from aqueous nanoparticulate dispersions. These films were printed over patterned silver interdigitated array designs for the purposes of conductimetric analysis. Unlike screen printing or lithography, inkjet printing does not require stencils or masks, therefore allowing rapid design and prototyping. For this study, polyaniline and modified polyaniline sensors were inkjet printed and assessed for the purposes of gas sensing applications, specifically hydrogen sulfide monitoring.
Direct Ascorbic Acid Detection With Ferritin Immobilized On Single-Walled Carbon Nanotubes, Chonlada Dechakiatkrai, Jun Chen, Carol M. Lynam, Kwang Min Shin, Seon Jeong Kim, Sukon Phanichphant, Gordon G. Wallace
Direct Ascorbic Acid Detection With Ferritin Immobilized On Single-Walled Carbon Nanotubes, Chonlada Dechakiatkrai, Jun Chen, Carol M. Lynam, Kwang Min Shin, Seon Jeong Kim, Sukon Phanichphant, Gordon G. Wallace
Gordon Wallace
Ferritin protein was noncovalently immobilized onto single-walled carbon nanotubes (SWNTs). This SWNT/ferritin composite was characterized using cyclic voltammetry, UV-visible spectroscopy, Raman spectroscopy, and high-resolution transmission electron microscopy. The use of the SWNT/ferritin film as an amperometric biosensor was demonstrated by sensing ascorbic acid in phosphate-buffered saline solution with a sensitivity of 767 uAmg. It demonstrated that ferritin protein bound to SWNTs enhances the oxidation reaction of ascorbic acid over 11-fold.
Mine Boundary Detection Using Partially Ordered Markov Models, Xia Hua, Jennifer Davidson, Noel A. Cressie
Mine Boundary Detection Using Partially Ordered Markov Models, Xia Hua, Jennifer Davidson, Noel A. Cressie
Professor Noel Cressie
Detection of objects in images in an automated fashion is necessary for many applications, including automated target recognition. In this paper, we present results of an automated boundary detection procedure using a new subclass of Markov random fields (MRFs), called partially ordered Markov models (POMMs). POMMs offer computational advantages over general MRFs. We show how a POMM can model the boundaries in an image. Our algorithm for boundary detection uses a Bayesian approach to build a posterior boundary model that locates edges of objects having a closed loop boundary. We apply our method to images of mines with very good …
A Car Detection System Based On Hierarchical Visual Features, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
A Car Detection System Based On Hierarchical Visual Features, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
Dr Fok Hing Chi Tivive
In this paper, we address the problem of detecting and localizing cars in still images. The proposed car detection system is based on a hierarchical feature detector in which the processing units are shunting inhibitory neurons. To reduce the training time and complexity of the network, the shunting inhibitory neurons in the first layer are implemented as directional nonlinear filters, whereas the neurons in the second layer have trainable parameters. A multi-resolution processing scheme is implemented so as to detect cars of different sizes, and to reduce the number of false positives during the detection stage, an adaptive thresholding strategy …
A Novel Template Matching Method For Human Detection, Duc Thanh Nguyen, Wanqing Li, Philip Ogunbona
A Novel Template Matching Method For Human Detection, Duc Thanh Nguyen, Wanqing Li, Philip Ogunbona
Associate Professor Wanqing Li
This paper proposes a novel weighted template matching method. It employs a generalized distance transform (GDT) and an orientation map (OM). The GDT allows us to weight the distance transform more on the strong edge points and the OM provides supplementary local orientation information for matching. Based on the matching method, a two-stage human detection method consisting of template matching and Bayesian verification is developed. Experimental results have shown that the proposed method can effectively reduce the false positive and false negative detection rates and perform superiorly in comparison to the conventional Chamfer matching method.
Kernel Pca Of Hog Features For Posture Detection, Peng Cheng, Wanqing Li, Philip Ogunbona
Kernel Pca Of Hog Features For Posture Detection, Peng Cheng, Wanqing Li, Philip Ogunbona
Associate Professor Wanqing Li
Motivated by the non-linear manifold learning ability of the Kernel Principal Component Analysis (KPCA), we propose in this paper a method for detecting human postures from single images by employing KPCA to learn the manifold span of a set of HOG features that can effectively represent the postures. The main contribution of this paper is to apply the KPCA as a non-linear learning and open-set classification tool, which implicitly learns a smooth manifold from noisy data that scatter over the feature space. For a new instance of HOG feature, its distance to the manifold that is measured by its reconstruction …
Human Detection Based On Weighted Template Matching, Duc Thanh Nguyen, Philip Ogunbona, Wanqing Li
Human Detection Based On Weighted Template Matching, Duc Thanh Nguyen, Philip Ogunbona, Wanqing Li
Associate Professor Wanqing Li
This paper proposes a new two-stage human detection method involving matching and verification. A Bayesian framework is developed to verify the matching score obtained from a weighted distance measure. Performance evaluation indicates that the proposed method is able to utilize the flexible matching scheme and produce superior true positive, true negative and low misclassification rates.
Human Detection With Contour-Based Local Motion Binary Patterns, Duc Thanh Nguyen, Philip Ogunbona, Wanqing Li
Human Detection With Contour-Based Local Motion Binary Patterns, Duc Thanh Nguyen, Philip Ogunbona, Wanqing Li
Associate Professor Wanqing Li
This paper presents a human detection method using contour- based local motion features. The local motion is encoded using a variant of the popular Local Binary Pattern (LBP) called Non-Redundant Local Binary Pattern (NRLBP) descriptor computed on the difference image of two consecutive frames. In addition, the local motion features are extracted along the human's boundary contour. Localising features on the contours has the advantage of utilizing a precise human shape description. A motivation of the proposed method is that most of informative movements are performed on boundary contours of the body parts, e.g. legs of pedestrians. Evaluation of the …
Smoke Detection In Videos Using Non-Redundant Local Binary Pattern-Based Features, Hongda Tian, Wanqing Li, Philip Ogunbona, Duc Thanh Nguyen, Ce Zhan
Smoke Detection In Videos Using Non-Redundant Local Binary Pattern-Based Features, Hongda Tian, Wanqing Li, Philip Ogunbona, Duc Thanh Nguyen, Ce Zhan
Associate Professor Wanqing Li
This paper presents a novel and low complexity method for real-time video-based smoke detection. As a local texture operator, Non-Redundant Local Binary Pattern (NRLBP) is more discriminative and robust to illumination changes in comparison with original Local Binary Pattern (LBP), thus is employed to encode the appearance information of smoke. Non-Redundant Local Motion Binary Pattern (NRLMBP), which is computed on the difference image of consecutive frames, is introduced to capture the motion information of smoke. Experimental results show that NRLBP outperforms the original LBP in the smoke detection task. Furthermore, the combination of NRLBP and NRLMBP, which can be considered …
Illumination Invariant Face Detection Using Classifier Fusion, Alister Cordiner, Philip Ogunbona, Wanqing Li
Illumination Invariant Face Detection Using Classifier Fusion, Alister Cordiner, Philip Ogunbona, Wanqing Li
Associate Professor Wanqing Li
An approach to the problem of illumination variations in face detection that uses classifier fusion is presented. Multiple face detectors are seperately trained for different illumination environments and their results are combined using a combination rule. To define the illumination environments, the training samples are clustered based on their illumination using unsupervised training. Different methods of clustering the samples and combining the outputs of the classifiers are examined. Experiments with the AR face database show that the proposed method achieves higher accuracy than the traditional monolithic face detection method.
A Novel Video-Based Smoke Detection Method Using Image Separation, Hongda Tian, Wanqing Li, Lei Wang, Philip Ogunbona
A Novel Video-Based Smoke Detection Method Using Image Separation, Hongda Tian, Wanqing Li, Lei Wang, Philip Ogunbona
Associate Professor Wanqing Li
In the state-of-the-art video-based smoke detection methods, the representation of smoke mainly depends on the visual information in the current image frame. In the case of light smoke, the original background can be still seen and may deteriorate the characterization of smoke. The core idea of this paper is to demonstrate the superiority of using smoke component for smoke detection. In order to obtain smoke component, a blended image model is constructed, which basically is a linear combination of background and smoke components. Smoke opacity which represents a weighting of the smoke component is also defined. Based on this model, …
Human Detection Using Local Shape And Non-Redundant Binary Patterns, Duc Thanh Nguyen, Wanqing Li, Philip Ogunbona
Human Detection Using Local Shape And Non-Redundant Binary Patterns, Duc Thanh Nguyen, Wanqing Li, Philip Ogunbona
Associate Professor Wanqing Li
Motivated by the advantages of using shape matching technique in detecting objects in various postures and viewpoints and the discriminative power of local patterns in object recognition, this paper proposes a human detection method combining both shape and appearance cues. In particular, local shapes of the body parts are detected using template matching. Based on body parts' shapes, local appearance features are extracted. We introduce a novel local binary pattern (LBP) descriptor, called Non-Redundant LBP (NRLBP), to encode local appearance of human. The proposed method was evaluated and compared with other state-of-the-art human detection methods on two commonly used datasets: …
An Improved Template Matching Method For Object Detection, Duc Thanh Nguyen, Wanqing Li, Philip Ogunbona
An Improved Template Matching Method For Object Detection, Duc Thanh Nguyen, Wanqing Li, Philip Ogunbona
Associate Professor Wanqing Li
This paper presents an improved template matching method that combines both spatial and orientation information in a simple and effective way. The spatial information is obtained through a generalized distance transform (GDT) that weights the distance transform more on the strong edge pixels and the orientation information is represented as an orientation map (OM) which is calculated from local gradient. We applied the proposed method to detect humans, cars, and maple leaves from images. The experimental results have shown that the proposed method outperforms the existing template matching methods and is robust against cluttered background.
Electrical Defect Detection In Thermal Image, Ahmed Haidar, Geoffrey Asiegbu, Kamarul Hawari, Faisal Ibrahim
Electrical Defect Detection In Thermal Image, Ahmed Haidar, Geoffrey Asiegbu, Kamarul Hawari, Faisal Ibrahim
Dr Ahmed Mohamed Ahmed Haidar
Electrical and Electronic objects, which have a temperature of operating condition above absolute zero, emit infrared radiation. This radiation can be measured on the infrared spectral band of the electromagnetic spectrum using thermal imaging. Faults on electrical systems are expensive in terms of plant downtime, damage, loss of production or risk from fire. If the threshold temperature is timely detected, the electrical equipment failures can be avoided. This paper presents a straightforward approach for thermal analysis that examines power loads and large area thermal characteristics. A thermal imaging camera was used to collect thermal pictures of the tested system under …
Ontology-Based Knowledge Representation For A P2p Multi-Agent Distributed Intrusion Detection System, Dayong Ye, Quan Bai, Minjie Zhang
Ontology-Based Knowledge Representation For A P2p Multi-Agent Distributed Intrusion Detection System, Dayong Ye, Quan Bai, Minjie Zhang
Associate Professor Minjie Zhang
Many research efforts on application of ontology in network security have been done in the past decade. However, they mostly stop at initial proposal or focus on framework design without detailed representation of intrusion or attack and relevant detection knowledge with ontology. In this paper, the design and implementation of ontology-based knowledge representation for a peer-to-peer multi-agent distributed intrusion detection system (ontology-based MADIDS) are introduced. An example which demonstrates the representation of an attack with ontology and the relevant detection process is also presented. In ontology-Based MADIDS, ontology technique enables peers in the system and agents in one peer to …
Fast Quality-Guided Phase Unwrapping Algorithm For 3d Profilometry Based On Object Image Edge Detection, Ke Chen, Jiangtao Xi, Yanguang Yu
Fast Quality-Guided Phase Unwrapping Algorithm For 3d Profilometry Based On Object Image Edge Detection, Ke Chen, Jiangtao Xi, Yanguang Yu
Dr Yanguang Yu
A main challenge associated with 3-dimentional fringe pattern profilometry (3D-FPP) systems is the unwrapping of phase maps resulted from complex object surface shapes with both robustness and speed guaranteed. In this paper we propose a new quality-guided phase unwrapping algorithm. In contrast to the conventional quality-guided methods, we classify pixels on wrapped phase map into two types by detecting edge pixels on object image: high quality (HQ) pixels corresponding to smooth phase changes and low quality (LQ) ones to rough phase changes. In order to improve the computational efficiency, these two types of pixels are unwrapped by means of different …
A Novel Video-Based Smoke Detection Method Using Image Separation, Hongda Tian, Wanqing Li, Lei Wang, Philip Ogunbona
A Novel Video-Based Smoke Detection Method Using Image Separation, Hongda Tian, Wanqing Li, Lei Wang, Philip Ogunbona
Dr Lei Wang
In the state-of-the-art video-based smoke detection methods, the representation of smoke mainly depends on the visual information in the current image frame. In the case of light smoke, the original background can be still seen and may deteriorate the characterization of smoke. The core idea of this paper is to demonstrate the superiority of using smoke component for smoke detection. In order to obtain smoke component, a blended image model is constructed, which basically is a linear combination of background and smoke components. Smoke opacity which represents a weighting of the smoke component is also defined. Based on this model, …
What Has My Classifier Learned? Visualizing The Classification Rules Of Bag-Of-Feature Model By Support Region Detection, Lingqiao Liu, Lei Wang
What Has My Classifier Learned? Visualizing The Classification Rules Of Bag-Of-Feature Model By Support Region Detection, Lingqiao Liu, Lei Wang
Dr Lei Wang
In the past decade, the bag-of-feature model has established itself as the state-of-the-art method in various visual classification tasks. Despite its simplicity and high performance, it normally works as a black box and the classification rule is not transparent to users. However, to better understand the classification process, it is favorable to look into the black box to see how an image is recognized. To fill this gap, we developed a tool called Restricted Support Region Set (RSRS) Detection which can be utilized to visualize the image regions that are critical to the classification decision. More specifically, we define the …