David A. Clausi

David A. Clausi
University of Waterloo | UWaterloo · Department of Systems Design Engineering

Professor

About

318
Publications
43,636
Reads
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8,333
Citations
Citations since 2017
80 Research Items
4142 Citations
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20172018201920202021202220230200400600
20172018201920202021202220230200400600
Introduction
Computer vision for various applications with an emphasis on remote sensing and sports analytics.
Skills and Expertise
Additional affiliations
July 1999 - present
University of Waterloo
Position
  • Professor (Full)

Publications

Publications (318)
Article
Algorithms designed for ice-water classification of synthetic aperture radar (SAR) sea ice imagery produce only binary (ice and water) output typically using manually labelled samples for assessment. This is limiting because only a small subset of labelled samples are used which, given the non-stationary nature of the ice and water classes, will li...
Article
Tracking and identifying players is a fundamental step in computer vision-based ice hockey analytics. The data generated by tracking is used in many other downstream tasks, such as game event detection and game strategy analysis. Player tracking and identification is a challenging problem since the motion of players in hockey is fast-paced and non-...
Article
Full-text available
Sea ice mapping plays an integral role in ship navigation and meteorological modeling in the polar regions. Numerous published studies in sea ice classification using synthetic aperture radar (SAR) have reported high classification rates. However, many of these focus on numerical results based on sample points and ignore the quality of the inferred...
Preprint
Full-text available
Tracking and identifying players is an important problem in computer vision based ice hockey analytics. Player tracking is a challenging problem since the motion of players in hockey is fast-paced and non-linear. There is also significant player-player and player-board occlusion, camera panning and zooming in hockey broadcast video. Prior published...
Article
Full-text available
Mapping soil heavy metal concentration using machine learning models based on readily available satellite remote sensing images is highly desirable. Accurate mapping relies on appropriate data, feature extraction, and model selection. To this end, a data processing pipeline for soil copper (Cu) concentration estimation has been designed. First, ins...
Article
Although the compact polarimetric (CP) synthetic aperture radar (SAR) mode of the RADARSAT Constellation Mission (RCM) offers new opportunities for oil spill candidate detection, there has not been an efficient machine learning model explicitly designed to utilize this new CP SAR data for improved detection. This paper presents a conditional random...
Preprint
Full-text available
Natural policy gradient methods are popular reinforcement learning methods that improve the stability of policy gradient methods by preconditioning the gradient with the inverse of the Fisher-information matrix. However, leveraging natural policy gradient methods in an optimal manner can be very challenging as many implementation details must be se...
Article
Automatic building footprint extraction from remote sensing imagery is a challenging task with important applications in geomatics and environmental science. Significant advances have been made in this field as a result of the emergence of deep convolutional neural networks (CNNs) designed for semantic segmentation. Although CNNs have demonstrated...
Article
Spectral unmixing (SU) plays a fundamental role in hyperspectral image (HSI) processing. Effective SU relies on the accurate and efficient characterization of the noise effect, the endmembers, and the spatial correlation effect in abundances, as well as efficient optimization techniques to estimate these effects. To address these issues, this artic...
Article
Full-text available
Soil moisture (SM) estimation is a critical part of environmental and agricultural monitoring, with satellite-based microwave remote sensing being the main SM source. However, the limited spatial resolution of most current remote sensing SM products reduces their utility for many applications, such as evapotranspiration modeling and agriculture man...
Article
Full-text available
Mapping different types of sea ice that form, grow, and melt in polar oceans is essential for shipping navigation, climate change modeling, and local community safety. Currently, ice charts are manually generated by analysts at the Canadian Ice Service (CIS) based on dual-polarized RADARSAT-2/RADARSAT Constellation Mission (RCM) imagery on a daily...
Preprint
Full-text available
Identifying players in video is a foundational step in computer vision-based sports analytics. Obtaining player identities is essential for analyzing the game and is used in downstream tasks such as game event recognition. Transformers are the existing standard in Natural Language Processing (NLP) and are swiftly gaining traction in computer vision...
Preprint
Full-text available
Advancements in attention mechanisms have led to significant performance improvements in a variety of areas in machine learning due to its ability to enable the dynamic modeling of temporal sequences. A particular area in computer vision that is likely to benefit greatly from the incorporation of attention mechanisms in video action recognition. Ho...
Preprint
Full-text available
Tracking and identifying players is a fundamental step in computer vision-based ice hockey analytics. The data generated by tracking is used in many other downstream tasks, such as game event detection and game strategy analysis. Player tracking and identification is a challenging problem since the motion of players in hockey is fast-paced and non-...
Preprint
Full-text available
Identifying players in sports videos by recognizing their jersey numbers is a challenging task in computer vision. We have designed and implemented a multi-task learning network for jersey number recognition. In order to train a network to recognize jersey numbers, two output label representations are used (1) Holistic - considers the entire jersey...
Article
Sentinel-1 is a synthetic aperture radar platform that provides free and open-source images of the Earth. A product type of Sentinel-1 is ground range detected (GRD), which records intensity while discarding phase information from the radar backscatter. Especially in cross-polarized GRD images, there are noticeable intensity changes throughout the...
Preprint
Full-text available
Sentinel-1 is a synthetic aperture radar (SAR) platform with an operational mode called extra wide (EW) that offers large regions of ocean areas to be observed. A major issue with EW images is that the cross-polarized HV and VH channels have prominent additive noise patterns relative to low backscatter intensity, which disrupts tasks that require m...
Article
Full-text available
The Canadian RADARSAT Constellation Mission (RCM) is represented by three synthetic aperture radar (SAR) satellites that each include a compact polarimetry (CP) mode. CP is advantageous because it provides increased backscatter information relative to single and conventional dual polarized modes and has larger swath widths relative to a quad polari...
Preprint
Full-text available
Puck localization is an important problem in ice hockey video analytics useful for analyzing the game, determining play location, and assessing puck possession. The problem is challenging due to the small size of the puck, excessive motion blur due to high puck velocity and occlusions due to players and boards. In this paper, we introduce and imple...
Article
Full-text available
Ice concentration estimates are typically acquired from algorithms using passive microwave satellite data, and from image analysis charts, but these have limitations. Estimates acquired from passive microwave data have coarse spatial resolution, may have errors due to atmospheric contamination, and often perform poorly in marginal ice zones. Image...
Preprint
Full-text available
In this work, an automatic and simple framework for hockey ice-rink localization from broadcast videos is introduced. First, video is broken into video-shots by a hierarchical partitioning of the video frames, and thresholding based on their histograms. To localize the frames on the ice-rink model, a ResNet18-based regressor is implemented and trai...
Article
The Cumberland Sound Beluga is a threatened population of belugas and the assessment of the population is done by a manual review of aerial surveys. The time-consuming and labor-intensive nature of this job motivates the need for a computer automated process to monitor beluga populations. In this paper, we investigate convolutional neural networks...
Article
In order to develop solutions for automatic ice rink localization from broadcast video, a dataset with ground truth homographies is required. Hockey broadcast video does not tend to provide camera parameters for each frame, which means that they must be gathered manually. A novel tool for collecting ground truth transforms through point corresponde...
Article
A critical step for computer vision-driven hockey ice rink localization from broadcast video is the automatic segmentation of lines on the rink. While the leveraging of segmentation methods for sports field localization has been previously explored, the design of deep neural networks for segmenting ice rink lines has not been well studied. Furtherm...
Article
Sentinel-1 is a synthetic aperture radar (SAR) platform with an operational mode called extra wide (EW) that offers large regions of ocean areas to be observed. A major issue with EW images is that the cross-polarized HV and VH channels have prominent additive noise patterns relative to low backscatter intensity, which disrupts tasks that require m...
Article
Synthetic aperture radar (SAR) sea ice imagery is a promising source of data for sea ice data assimilation. Classification of SAR sea ice imagery into ice and water is of particular relevance due to its relationship with ice concentration, a key variable in sea ice data assimilation systems. With increasing volumes of SAR data, automated methods to...
Article
Full-text available
Changes to ice cover on lakes throughout the northern landscape has been established as an indicator of climate change and variability, expected to have implications for both human and environmental systems. Monitoring lake ice cover is also required to enable more reliable weather forecasting across lake-rich northern latitudes. Currently, the Can...
Article
Although efficient hyperspectral image (HSI) denoising relies on complete and accurate description and modeling the spatial-spectral signal in HSI, the current approaches do not fully account for key characteristics of HSI, i.e., the mixed spectra effect, the spatial nonstationarity effect, and noise variance heterogeneity effect. To address this i...
Article
Although accurate training and initialization information is difficult to acquire, unsupervised hyperspectral subpixel mapping (SPM) without relying on this predefined information is an insufficiently addressed research issue. This letter presents a novel Bayesian approach for unsupervised SPM of hyperspectral imagery (HSI) based on the Markov rand...
Preprint
Full-text available
Puck location in ice hockey is essential for hockey analysts for determining the location of play and analyzing game events. However, because of the difficulty involved in obtaining accurate annotations due to the extremely low visibility and commonly occurring occlusions of the puck, the problem is very challenging. The problem becomes even more c...
Preprint
Full-text available
In problems such as sports video analytics, it is difficult to obtain accurate frame level annotations and exact event duration because of the lengthy videos and sheer volume of video data. This issue is even more pronounced in fast-paced sports such as ice hockey. Obtaining annotations on a coarse scale can be much more practical and time efficien...
Article
Full-text available
Lung cancer is the leading cause of cancer-related death worldwide. Computer-aided diagnosis (CAD) systems have shown significant promise in recent years for facilitating the effective detection and classification of abnormal lung nodules in computed tomography (CT) scans. While hand-engineered radiomic features have been traditionally used for lun...
Chapter
In this paper, we present a novel approach called KPTransfer for improving modeling performance for keypoint detection deep neural networks via domain transfer between different keypoint subsets. This approach is motivated by the notion that rich contextual knowledge can be transferred between different keypoint subsets representing separate domain...
Conference Paper
Full-text available
In this paper, a novel two-stream architecture has been designed to improve action recognition accuracy for hockey using three main components. First, pose is estimated via the Part Affinity Fields model to extract meaningful cues from the player. Second, optical flow (using LiteFlownet) is used to extract temporal features. Third, pose and optical...
Article
Automatic classification methods using satellite imagery are beneficial in the sea-ice-type mapping of the Arctic regions. In the near future, the RADARSAT Constellation Mission (RCM) will be launched, providing unique compact polarimetric (CP) synthetic aperture radar (SAR) data, expected to be an improvement over the current RADARSAT-2 dual-polar...
Preprint
In this paper, we address the hyperspectral image (HSI) classification task with a generative adversarial network and conditional random field (GAN-CRF) -based framework, which integrates a semi-supervised deep learning and a probabilistic graphical model, and make three contributions. First, we design four types of convolutional and transposed con...
Article
Full-text available
In this paper, we address the hyperspectral image (HSI) classification task with a generative adversarial network and conditional random field (GAN-CRF)-based framework, which integrates a semi-supervised deep learning and a probabilistic graphical model and make three contributions. First, we design four types of convolutional and transposed convo...
Preprint
In this paper, we present a novel approach called KPTransfer for improving modeling performance for keypoint detection deep neural networks via domain transfer between different keypoint subsets. This approach is motivated by the notion that rich contextual knowledge can be transferred between different keypoint subsets representing separate domain...
Article
Full-text available
Despeckling of synthetic aperture radar (SAR) is a known research challenge. A novel solution to this problem has been developed and evaluated via an iterative maximum a posterior estimation incorporating a Bayesian joint decorrelation and despeckling based on a correlation model. This model realistically explores the physical correlation process o...
Article
Full-text available
Accurate estimates of sharp features in the sea ice cover, such as leads and ridges, are critical for shipping activities, ice operations and weather forecasting. These sharp features can be difficult to preserve in data fusion and data assimilation due to the spatial correlations in the background error covariance matrices. In this article, a set...
Preprint
Objective: Lung cancer is the leading cause of cancer-related death worldwide. Computer-aided diagnosis (CAD) systems have shown significant promise in recent years for facilitating the effective detection and classification of abnormal lung nodules in computed tomography (CT) scans. While hand-engineered radiomic features have been traditionally u...
Preprint
Full-text available
Recognizing actions in ice hockey using computer vision poses challenges due to bulky equipment and inadequate image quality. A novel two-stream framework has been designed to improve action recognition accuracy for hockey using three main components. First, pose is estimated via the Part Affinity Fields model to extract meaningful cues from the pl...
Article
Full-text available
Lake ice is a significant component of the cryosphere due to its large spatial coverage in high-latitude regions during the winter months. The Laurentian Great Lakes are the world’s largest supply of freshwater and their ice cover has a major impact on regional weather and climate, ship navigation, and public safety. Ice experts at the Canadian Ice...
Article
Typical unsupervised classification of hyperspectral imagery (HSI) uses a Gaussian mixture model to determine intensity similarity of pixels. However, the existence of mixed pixels in HSI tends to reduce the effectiveness of the similarity measure and leads to large classification errors. Since a semantic class is always dominated by a particular e...
Article
Full-text available
Heavy metal pollution is a critical global environmental problem which has always been a concern. Traditional approach to obtain heavy metal concentration relying on field sampling and lab testing is expensive and time consuming. Although many related studies use spectrometers data to build relational model between heavy metal concentration and spe...
Article
Full-text available
Dual-polarized airborne passive microwave (PM) brightness temperatures (Tb) at 6.9 GHz H/V, 19 GHz H/V and 37 GHz H/V and spaceborne active microwave (AM) X-band (9.65 GHz VV, VH) backscatter (σ⁰) are observed coincident to in situ snow and lake-ice measurements collected over two lakes near Inuvik, Canada. Lake-ice thickness is found to be positiv...
Article
Full-text available
Automated analysis of broadcast soccer game video is a challenging computer vision problem. Prior to performing high-level analysis (such as event detection), accurate classification of shot views and play-break segmentation are required to analyze the structure of soccer video. A novel deep network called parallel feature fusion network (PFF-Net)...
Article
The problem of limited labeled training samples is challenging for the classification of remote sensing imagery. We develop a joint classification and segmentation algorithm to address this problem. Our algorithm combines semisupervised learning and conditional random fields (CRFs) into a single framework. The multimodal Gaussian maximum-likelihood...
Article
A novel approach for inferring depth measurements via multispectralactive depth from defocus and deep learning has been designed,implemented, and successfully tested. The scene is activelyilluminated with a multispectral quasi-random point pattern,and a conventional RGB camera is used to acquire images of theprojected pattern. The projection points...
Article
Full-text available
This paper intends to find a more cost-effective way for training oil spill classification systems by introducing active learning (AL) and exploring its potential, so that satisfying classifiers could be learned with reduced number of labeled samples. The dataset used has 143 oil spills and 124 look-alikes from 198 RADARSAT images covering the east...
Article
With the fast advancement of remote sensing platforms and sensors, remotely sensed imagery (RSI) is increasingly being characterized by both high spatial resolution and high temporal resolution. How to efficiently use the rich spatial and temporal information in RSI for highly accurate object detection and classification is an important research qu...