Qigang Gao

Qigang Gao
Dalhousie University | Dal · Faculty of Computer Science

About

76
Publications
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690
Citations

Publications

Publications (76)
Article
Bag of visual words (BoVW) models are widely utilized in image/ video representation and recognition. The cornerstone of these models is the encoding stage, in which local features are decomposed over a codebook in order to obtain a representation of features. In this paper, we propose a new encoding algorithm by jointly encoding the set of local d...
Conference Paper
Full-text available
As predictive marketing and customer profiling solutions have become more sophisticated, they have increasingly become dependent on data from external sources. In order to utilize this data, records must be linked to internal records without the use of unique identifiers. The Extendable Logic for Matching (ELM) performs probabilistic matching from...
Conference Paper
In the context of human action recognition using skeleton data, the 3D trajectories of joint points may be considered as multi-dimensional time series. The traditional recognition technique in the literature is based on time series dis(similarity) measures (such as Dynamic Time Warping). For these general dis(similarity) measures, k-nearest neighbo...
Conference Paper
The demand for gesture/action recognition technologies has been increased in the recent years. State-of-the-art systems of gesture/action recognition have been using low-level features or intermediate bag-of-features as gesture/action descriptors. Those methods ignore the spatial and temporal information on shape and internal structures of the targ...
Chapter
Over the years, many networks hosted by large companies or organizations have been crippled by intrusions launched with minimal effort. Such attacks have caused the loss of millions of dollars for the company and created serious security threats. As a result, network administrators and security experts across the globe have barricaded their network...
Article
Multiple classifier systems, also known as classifier ensembles, have received great attention in recent years because of their improved classification accuracy in different applications. In this paper, we propose a new general approach to ensemble classification, named generic subclass ensemble, in which each base classifier is trained with data b...
Article
The performance of different action-recognition methods using skeleton joint locations have been recently studied by several computer vision researchers. However, the potential improvement in classification through classifier fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of five a...
Conference Paper
Efficient and reliable human tracking in arbitrary environments is challenging, as there is currently no single solution that can successfully handle all scenarios. In this paper we present a novel approach that uses a top view 3D camera, which employs a simplified yet expressive human body model for effective multi-target detection and tracking. B...
Article
The unprecedented explosion of real-life big data sets have sparked a lot of research interests in data mining in recent years. Many of these big data sets are generated in network environment and are characterized by a dauntingly large size and high dimensionality which pose great challenges for detecting useful knowledge and patterns, such as net...
Article
Pairwise classification is a well-known class binarization technique that converts a multiclass problem into a number of two-class problems, one problem for each pair of classes. However, in the pairwise technique, nuisance votes of many irrelevant classifiers may result in a wrong class prediction. To overcome this problem, a simple, but efficient...
Conference Paper
Rapid growth of visual data processing and analysis applications, such as content based image retrieval, augmented reality, automated inspection and defect detection, medical image understanding, and remote sensing has made the problem of developing accurate and efficient image representation and classification methods one of the key research areas...
Article
Full-text available
Click here and insert your abstract text. Search engine advertising has become one of the most important revenue models of electronic commerce. It strongly affects the probability that users click on the ads at the side of the search results page if the system shows the right ones. To maximize the outcome of search engine revenue and improve percep...
Article
Full-text available
Currently, many database applications deal with large imprecise and uncertain datasets. Probabilistic data summarization has recently emerged and has already become an active research area in the database community. In this paper, we propose a data summarization method to summarize multidimensional probabilistic data using histograms. The proposed...
Conference Paper
Multiple classifier systems, also known as classifier ensembles, have received great attention in recent years because of the improved classification accuracy in different applications. A large variety of ensemble methods have been proposed in order to exploit strengths of individual classifiers. In this paper, we present a unifying framework for m...
Article
Two key factors affecting the performance of Error Correcting Output Codes (ECOC) in multiclass classification problems are the independence of binary classifiers and the problem-dependent coding design. In this paper, we propose an evolutionary algorithm-based approach to the design of an application-dependent codematrix in the ECOC framework. The...
Conference Paper
The performance of different feature extraction and shape description methods in trademark image recognition systems have been studied by several researchers. However, the potential improvement in classification through feature fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of thre...
Conference Paper
Among the proposed methods to deal with multi-class classification problems, the Error-Correcting Output Codes (ECOC) represents a powerful framework. The key factor in designing any ECOC matrix is the independency of the binary classifiers, without which the ECOC method would be ineffective. This paper proposes an efficient new approach to the ECO...
Article
Individual classification models have recently been challenged by ensemble of classifiers, also known as multiple classifier system, which often shows better classification accuracy. In terms of merging the outputs of an ensemble of classifiers, classifier selection has not attracted as much attention as classifier fusion in the past, mainly becaus...
Conference Paper
The pairwise classification approach tends to perform better than other well-known approaches when dealing with multiclass classification problems. In the pairwise approach, however, the nuisance votes of many irrelevant classifiers may result in a wrong prediction class. To overcome this problem, a novel method, Local Crossing Off (LCO), is presen...
Conference Paper
Logo recognition is an important task in the field of document image processing and retrieval. Successful recognition of logos facilitates automatic classification of source documents, which has been considered as a key strategy for document image analysis. From machine learning point of view, logo recognition may be considered as a multi-class cla...
Article
E-commerce has made great strides in providing a convenient, fast and secure shopping experience for consumers. However, there is still a significant portion of shoppers whose security fears impact how they spend their money online. Because of this, security issues associated with ecommerce and customer sites must be constantly reviewed and updated...
Conference Paper
Full-text available
Business leads generation is a crucial and challenging task for online business to attract customers and improve their services. This paper presents a case study of an online real estate service company which provides potential home buyers useful neighborhood information, and accordingly offers them business leads to real estate companies. The comp...
Conference Paper
Human vision can perceive body movements and actions effortlessly. In contrast, it is still a very challenging task for machines to have comparable performance. Many research results have shown that both visual attention and perceptual organization are crucial for visual perception tasks. In recent years, gesture recognition for HCI has drawn more...
Article
Human body motion and gesture analysis has been boosted by the latest developments of 3D cameras and the high demands of emerging applications. Body parts classification and pose estimation are essential for the human body tracking and motion recognition. In this poster, we present a 3D perceptual shape feature-based approach for efficient body par...
Conference Paper
This paper presents a framework of gesture recognition and tracking using 3D camera, edge features and particle filters. A target gesture is modeled with perceptual shape features qualitatively. The perceptual model is used to guide tracking based on a particle filtering method to achieve reliable results. The system has been applied to a video gam...
Article
In this paper, we study the problem of anomaly detection in wireless network streams. We have developed a new technique, called Stream Projected Outlier deTector (SPOT), to deal with the problem of anomaly detection from multi-dimensional or high-dimensional data streams. We conduct a detailed case study of SPOT in this paper by deploying it for an...
Conference Paper
This paper employs SPOT (Stream Projected Outlier deTector) as a prototype system for anomaly-based intrusion detection and evaluates its performance against other major methods. SPOT is capable of processing high-dimensional data streams and detecting novel attacks which exhibit abnormal behavior, making it a good candidate for network intrusion d...
Conference Paper
Generic shape feature extraction is a challenging task for image and video content analysis. We present a non-parametric statistics based method for extracting generic shape tokens based on a Perceptual Curve Partition and Grouping (PCPG) model. In this PCPG model, each curve is made up of Generic Edge Tokens (GET) connected at Curve Partitioning P...
Conference Paper
Detecting outliers from high-dimensional data is a challenge task since outliers mainly reside in various low-dimensional subspaces of the data. To tackle this challenge, subspace analysis based outlier detection approach has been proposed recently. Detecting outlying subspaces in which a given data point is an outlier facilitates a better characte...
Conference Paper
Full-text available
In this paper, we study the problem of projected outlier detection in high di- mensional data streams and propose a new technique, called Stream Projected Ouliter deTector (SPOT), to identify outliers embedded in subspaces. Sparse Subspace Tem- plate (SST), a set of subspaces obtained by unsupervised and/or supervised learn- ing processes, is const...
Conference Paper
CBIR has been an active topic for more than one decade. Current systems still lack in flexibility and accuracy because of semantic gap between image’s feature-level and semantic-level representations. Although many techniques have been developed for automatic or semi-automatic retrieval (e.g. interactive browsing, relevance feedback (RF)), issues a...
Conference Paper
In this paper, we study the problem of anomaly detection in high-dimensional network streams. We have developed a new technique, called Stream Projected Outlier deTector (SPOT), to deal with the problem of anomaly detection from high-dimensional data streams. We conduct a case study of SPOT in this paper by deploying it on 1999 KDD Intrusion Detect...
Conference Paper
Curve detection is one of the fundamental steps in computer vision applications. Conventional edge detectors provide only an output of edge pixels; curve matching is then needed to fit edge pixels into curves. Despite having achieved some success, it suffers constraints for applications that require real-time and robust image analysis, such as robo...
Conference Paper
In this paper, we present a new technique, called stream projected ouliter detector (SPOT), to deal with outlier detection problem in high-dimensional data streams. SPOT is unique in a number of aspects. First, SPOT employs a novel window-based time model and decaying cell summaries to capture statistics from the data stream. Second, sparse subspac...
Article
Full-text available
Discovering gene co-regulatory relationships is one of most important research in DNA microarray data analysis. The problem of gene specific co-regulation discovery is to, for a particular gene of interest (called target gene), identify the condition subsets where strong gene co-regulations of the target gene are observed and its co-regulated genes...
Conference Paper
Human visual recognition is based largely on shape, yet effectively using shapes in natural image retrieval is a challenging task. Most existing methods are based on the geometric equations of curves computed from processing an entire image. These processes are computationally intensive, lack flexibility and do not take advantage or with minimum us...
Article
Perceptual organization based methods were used to classify edge features of an image as straight line, curve, or noise. Based upon Gao and Wang's curve detection methods, we achieved more accurate edge partitioning and edge feature extraction. Using per- ceptual classification rules, these edge features were classified into the three categories. T...
Conference Paper
Detecting outlying subspaces is a relatively new research problem in outlier-ness analysis for high-dimensional data. An outlying subspace for a given data point p is the sub- space in which p is an outlier. Outlying subspace detection can facilitate a better characterization process for the de- tected outliers. It can also enable outlier mining fo...
Conference Paper
Abstract The problem of gene specific co-regulation discovery is that, for a particular gene of interest, identify its closely co- regulated genes and the associated subsets of experimen- tal conditions in which such co-regulations occur. The co- regulations are local in the sense that they occur in some subsets of full experimental conditions. In...
Conference Paper
This paper presents a perceptual organization based method for real-time license plate identification and tracking by video content analysis. In this method, video content is described using a set of perceptual shape features, called generic edge tokens (GET). A video frame can be represented as a GET map. Motion GETs (MGETs) are segmented from the...
Conference Paper
The performance of a classification algorithm in data mining is greatly affected by the quality of data source. Irrelevant and redundant features of data not only increase the cost of mining process, but also degrade the quality of the result in some cases. This issue is particularly important to high-dimensional data, in that many features may eit...
Conference Paper
Full-text available
Currently in document retrieval there are many algorithms each with different strengths and weakness. There is some difficulty, however, in evaluating the impact of the test query set on retrieval results. The traditional evaluation process, the Cranfield evaluation paradigm, which uses a corpus and a set of user queries, focuses on making the quer...
Article
In this paper, we present a perceptual organization-based method for detecting moving objects from image sequences. To achieve the characteristics of real-time, efficiency, and robustness, a perceptual computation model of edge partitioning and grouping was proposed for the extraction of edge traces on the fly. Each edge trace is made up of generic...
Conference Paper
A key issue of content-based image retrieval is exploring how to bridge the gap between the high-level semantics of an image and its lower-level properties, such as color, texture and edge. In this paper, we present a new method using perceptual edge features, called generic edge tokens (GET), as image shape content descriptors for CBIR. GETs repre...
Article
This study was designed to test a cumulative view of current data in the clinical database at the Faculty of Dentistry, Dalhousie University. We planned to examine associations among demographic factors and treatments. Three tables were selected from the database of the faculty: patient, treatment and procedures. All fields and record numbers in ea...
Conference Paper
One of the effects of the general Internet growth is an immense number of user accesses to WWW resources. These accesses are recorded in the web server log files, which are a rich data resource for finding useful patterns and rules of user browsing behavior, and they caused the rise of technologies for Web usage mining. Current Web usage mining app...
Conference Paper
Full-text available
The Pediatric Pain Mailing List (PPML) is an international Internet-based forum for informal discussion of any topic related to pain in children. There are now over seven hundred members, including clinicians, researchers and patients from at least forty countries on six continents. Currently, the archive contains more than ten thousand messages. T...
Conference Paper
Image region detection aims to extract meaningful regions from image. This task may be achieved equivalently by finding the interior or boundaries of regions. The advantage of the second strategy is that once a closure is detected not only its shape information is available, but also the interior property can be estimated with a minimum effort. In...
Conference Paper
We present a perceptual organization based on method for motion stream analysis. The computation model was developed based upon a perception principle: visual feature partitioning and grouping. In the method, perceptual edge features are extracted and classified into generic edge tokens (GETs) using edge tracking and partitioning on the fly. GETs a...
Conference Paper
This paper presents a perceptual organization based method for the representation and extraction of junction structures of edge segments from digital images. Perceptual Junctions (PJs) are higher-level view invariant feature entities, which are made up by intersected generic edge tokens including both linear and non-linear segments. The class of lo...
Article
This paper presents a new type of computer interface to large population health-care data repositories via the Internet. It does not require programming knowledge but is flexible enough to handle the ad-hoc queries common in research settings. The interface allows for the automated creation of SAS programs by the end users using a GUI-based questio...
Conference Paper
This paper presents a method for detecting moving objects in image sequences produced by a stationary camera. The method is based on perceptual organisation. An edge tracker is developed to extract edge traces on the fly. It is both robust and fast; the method executes in real-time. Moving objects are detected and tracked within the image sequence...
Conference Paper
This paper presents a fuzzy logic approach for classifying generic edge segments (GES). A set of GES is modeled in descriptive geometry based on perceptual organization principles. Each GES represents a class of edge segments which belong to a same perceptual group and measured according to the generic criteria of perceptual organization laws. A fu...
Conference Paper
Presents a neural network method for partitioning image curves into perceptual entities called generic curve segments (GCSs). GCSs are perceptual classes of primitive curve objects, which are qualitative descriptors for grouping curve shapes. The success of GCS classification and curve grouping relies on correctly locating curve partitioning points...
Conference Paper
This paper presents a generic approach of visual knowledge representation for man-made object recognition based on perceptual organization. In the approach, a generic model scheme is developed for coding both perceptual structures of objects and generic viewing situations of the objects in a qualitative manner. A set of generic edge features are de...
Article
The visual appearance of an object in space is an image configuration projected from a subset of connected faces of the object. It is believed that face perception and face integration play a key role in object recognition in human vision. This paper presents a novel approach for calculating viewpoint consistency for three-dimensional (3D) object r...
Article
A computational model for recognition of three-dimensional (3-D) man-made objects based on visual perception principles is presented. In this approach, object faces are used as perceptual entities in accordance with the perceptual phenomena of face-shape constancy and face-pose consistency. Face-shape constancy is modeled by continuous maps in whic...
Conference Paper
Presents an algorithm and representation scheme for extracting structure tokens of cephalograms directly from X-ray images. The method is based on a principle of visual perception, i.e., edge partitioning and grouping which simulates human visual process on edge perception in certain aspects. With the method, image edges are first traced and partit...
Article
A curve detection method is described based on the perceptual organization of descriptive curve features. A set of curve partitioning and grouping rules is derived for detecting image curves. With these rules, this method is capable of tracking curve segments and joining them into an appropriate form of curve structure according to its topological...
Article
This paper presents an effective corner detector based on perceptual organization and a curve tracking scheme. The detector first finds 2-D corners among the curve partitioning points. It then locates 3-D corners by detecting the terminations of tracked curves intersecting at 2-D corners. It then assigns an attribute value according to its perceptu...
Article
This paper presents a geometric reasoning approach to detect image curves. A set of curve partitioning and grouping rules is derived based on perceptual organization of curve features. This method is capable of tracing curve segments and joining them into an appropriate form of curve structure according to its topological and geometric properties....
Article
This paper presents a perceptual organization based method for detecting Vessel Junctions (VJs) from retinal images. A retinal image is first segmented into edge traces which contain vessel boundaries. Each trace is divided into generic curve segments (GCSs) at curve partitioning points (CPPs). CPPs are the places on a trace from where the continui...
Article
This paper presents a perceptual organization based method for describing, extracting and grouping generic edge features, called Generic Edge Tokens (GET). A GET is a perceptually significant image primitive which represents a class of qualitatively equivalent structure elements. A complete set of GETs includes both linear and non-linear segment cl...
Article
Over-segmentation of edge features has been a chal- lenging problem for many edge-based vision applica- tions. Too many useless features are simply back- ground noise which are costly for higher-level process- ing. The conventional methods of dealing with over- segmentation use various noise suppressing filters at pixel level for the entire image,...
Article
The explosion of data streams has sparked a lot of research interests in data mining on streaming data flow in recent years. Many data streams are inherently high dimen-sional and outlier detection from these data streams can potentially lead to discovery of useful abnormal and irregular patterns hidden in the streams. Outlier detection in data str...