A Tool for Annotating Homographies from Hockey Broadcast Video

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 correspondences between each frame and an overhead view of the ice rink is presented in this paper. Through collaboration with the users of the tool, we have added features to improve accuracy and efficiency, especially in frames with few lines on the playing surface visible. A dataset of 4,262 frames has been collected, which will be used for research into automatic camera calibration techniques.

BenderNet and RingerNet: Highly Efficient Line Segmentation Deep Neural Network Architectures for Ice Rink Localization

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. Furthermore, the exploration of efficient architecture designs is very important given the operational requirements of real-time sports analytics. Motivated by this, BenderNet and RingerNet, two highly efficient deep neural network architectures, have been designed specifically for ice rink line segmentation. Experiments on a dataset of annotated NHL broadcast video demonstrate high accuracy while maintaining high model efficiency, thus making the proposed methods well-suited for real-time ice hockey rink localization.

Badminton player detection using faster region convolutional neural network

Nowadays, coaches and sport analyst are concerning about sport performance analysis through sport video match. However, they still used conventional method which is through manual observation of the full video that is very troublesome because they might miss some meaningful information presence in the video. Several previous studies have discussed about tracking ball movements, identification of player based on jersey color and number as well as player movement detection in various type of sport such as soccer and volleyball but not in badminton. Therefore, this study focused on developing an automated system using Faster Region Convolutional Neural Network (Faster R-CNN) to track the position of the badminton player from the sport broadcast video. In preparing the dataset for training and testing, several broadcast videos were converted into image frames before labelling the region which indicate the players. After that, several different trained Faster R-CNN detectors were produced from the dataset before tested with different set of videos to evaluate the detector performance. In evaluating the performance of each detector model, the average precision was obtained from precision recall graph. As a result, this study revealed that the detector successfully detects the player when the detector is being fed with more generalized dataset.

Social surveillance and Let’s Play: A regional case study of gaming in Manila slum communities

This article examines the use of Let’s Play (LP) in Manila, Philippines. LP is an emerging genre in which players record, narrate, and broadcast video game play online. While in Western contexts LP is predominantly viewed in domestic settings, our focus is on the distinct manner in which LP is viewed in the Philippines, resulting in unique social architectures of play that coalesce public and private practices. In particular, the arcade-style vending machine, pisonet (a conflation between the Filipino piso [currency] + inter[net]), plays a key role in shaping net cultures within everyday life. Through the pisonet, unique forms of performative play happen in and around the watching play of LP. These types of performativity around LP see intergenerational and public forms of play, spectatorship, and surveillance entangle. Drawing on ethnographic research conducted in Metropolitan Manila, this study aims to conceptualize how public spaces, screens, and play—through the LP on pisonets—bring about unique modes of sociality and surveillance of care. In doing so, this paper complicates established viewership models of LP, exploring how their manifestation in Manila gives rise to a particular type of Filipino sense of play.

Pengamanan Acakan Biss Menggunakan Algoritma RSA

BISS scramble method is a method in which description is done before the broadcast frequency signal sent to each TV station. This is done so that the delivery system and a broadcast signal receiving premium can be gated. BISS scramble method combined with RSA (Rivest Shamir Adleman), which later on safety in the delivery and receiving radio frequency signals broadcast video files can be gated and more robust against an attack.