Mehrnaz Fani

Mehrnaz Fani
University of Waterloo | UWaterloo · Dept. of System Design Engineering

PhD

About

21
Publications
2,382
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
129
Citations
Citations since 2017
15 Research Items
128 Citations
2017201820192020202120222023010203040
2017201820192020202120222023010203040
2017201820192020202120222023010203040
2017201820192020202120222023010203040
Additional affiliations
September 2011 - December 2015
Shiraz University
Position
  • PhD Student

Publications

Publications (21)
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-...
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...
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...
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
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...
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
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
In this work, a convolutional neural network (CNN) has been designed to interpret player actions in ice hockey video. The hourglass network is employed as the base to generate player pose estimation and layers are added to this network to produce action recognition. As such, the unified architecture is referred to as action recognition hourglass ne...
Conference Paper
Template matching is a widely used technique in many of image processing and machine vision applications. In this paper we propose a new as well as a fast and reliable template matching algorithm which is invariant to Rotation, Scale, Translation and Brightness (RSTB) changes. For this purpose, we adopt the idea of ring projection transform (RPT) o...
Article
Full-text available
Template matching is a widely used technique in many of image processing and machine vision applications. In this paper we propose a new as well as a fast and reliable template matching algorithm which is invariant to Rotation, Scale, Translation and Brightness (RSTB) changes. For this purpose, we adopt the idea of ring projection transform (RPT) o...
Conference Paper
Full-text available
Image super-resolution is a technique of combining a set of overlapping low-resolution (LR) images to produce a high-resolution (HR) image. This technique has two main steps; the first step is alignment of LR images that should be done with sub-pixel accuracy and the second step is the reconstruction stage. In this paper, we improve the works done...

Network

Cited By

Projects

Projects (2)
Project
Player tracking, event detection and pose estimation in hockey using computer vision and deep learning.
Project
I try to use deep networks, esp. Autoencoders, for feature extraction in images and videos.... this practice is so popular today but i try to adopt it for my specific purpose.