Intelligent filtering by semantic importance for single-view 3D reconstruction from Snooker video

Legg, Phil; Parry, Matthew L.; Chung, David; Jiang, Richard; Morris, Allison; Griffiths, Iwan W.; Marshall, David; Chen, Min

doi:10.1109/icip.2011.6116122

Cited by 8 publications

(9 citation statements)

References 9 publications

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“…However, our system works in real time and in real conditions, whereas systems like Refs. [2,4,22] work with video (or video streams) taken from pool or snooker championships, with very stable and controlled conditions (lighting, player positions, etc. ), or expect a controlled environment because of the use of robots [5][6][7].…”

Section: Discussionmentioning

confidence: 99%

Augmented reality system to assist inexperienced pool players

2016

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Pool and billiards are amongst a family of games played on a table with six pockets along the rails. This paper presents an augmented reality tool designed to assist unskilled or amateur players of such games. The system is based on a projector and a Kinect 2 sensor placed above the table, acquiring and processing the game on-the-fly. By using depth information and detecting the table's rails (borders), the balls' positions, the cue direction, and the strike of the ball, computations predict the resulting balls' trajectories after the shot is played. These resultstrajectories, visual effects, and menus-are visually output by the projector, making them visible on the snooker table. The system achieves a shot prediction accuracy of 98% when no bouncing occurs.

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Section: Discussionmentioning

confidence: 99%

Augmented reality system to assist inexperienced pool players

2016

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“…A comprehensive overview for performing 3D reconstruction is described by Hartley and Zisserman [15]. Our technique is based on the work by Legg et al [21] for single-camera reconstruction of a snooker scene using projective transformation given any arbitrary table view.…”

Section: D Reconstructionmentioning

confidence: 99%

“…More significantly, snooker clubs and academies have yet to benefit from such technology due to the cost of installation (e.g., around £200,000 for Hawk-eye). To facilitate our target users, we propose error analysis on a more flexible system using a single camera [21]. One desirable ability is to review a sequence of training shots [29] to support performance analysis.…”

Section: Camera Sensitivity and Error Derivationmentioning

confidence: 99%

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Visualizing multiple error-sensitivity fields for single camera positioning

Chung

Parry

Legg

et al. 2012

Comput. Visual Sci.

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In many data acquisition tasks, the placement of a real camera can vary significantly in complexity from one scene to another. Optimal camera positioning should be governed not only by least error sensitivity, but in addition to real-world practicalities given by various physical, financial and other types of constraints. It would be a laborious and costly task to model all these constraints if one were to rely solely on fully automatic algorithms to make the decision. In this work, we present a study using 2D and 3D visualization methods to assist in single camera positioning based on error sensitivity of reconstruction and other physical and financial constraints. We develop a collection of visual mappings that depict the composition of multiple error sensitivity fields that occur for a given camera position. Each camera position is then mapped to a 3D visualization that enables visual assessment of the camera configuration. We find that the combined 2D and

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“…The process of detecting, classifying and tracking each ball object within the captured scene (Fig. 6) is given in [15]. For each shot in the match, and each frame of video in the shot, we obtain the following data for each ball: ID, colour, position, speed, direction.…”

Section: System Overviewmentioning

confidence: 99%

Hierarchical Event Selection for Video Storyboards with a Case Study on Snooker Video Visualization

Parry

Legg

Chung

et al. 2011

IEEE Trans. Visual. Comput. Graphics

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Disclaimer UWE has obtained warranties from all depositors as to their title in the material deposited and as to their right to deposit such material. UWE makes no representation or warranties of commercial utility, title, or fitness for a particular purpose or any other warranty, express or implied in respect of any material deposited.UWE makes no representation that the use of the materials will not infringe any patent, copyright, trademark or other property or proprietary rights. UWE accepts no liability for any infringement of intellectual property rights in any material deposited but will remove such material from public view pending investigation in the event of an allegation of any such infringement. Abstract-Video storyboard, which is a form of video visualization, summarizes the major events in a video using illustrative visualization. There are three main technical challenges in creating a video storyboard, (a) event classification, (b) event selection and (c) event illustration. Among these challenges, (a) is highly application-dependent and requires a significant amount of applicationspecific semantics to be encoded in a system or manually specified by users. This paper focuses on challenges (b) and (c). In particular, we present a framework for hierarchical event representation, and an importance-based selection algorithm for supporting the creation of a video storyboard from a video. We consider the storyboard to be an event summarization for the whole video, whilst each individual illustration on the board is also an event summarization but for a smaller time window. We utilized a 3D visualization template for depicting and annotating events in illustrations. To demonstrate the concepts and algorithms developed, we use Snooker video visualization as a case study, because it has a concrete and agreeable set of semantic definitions for events and can make use of existing techniques of event detection and 3D reconstruction in a reliable manner. Nevertheless, most of our concepts and algorithms developed for challenges (b) and (c) can be applied to other application areas.

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Intelligent filtering by semantic importance for single-view 3D reconstruction from Snooker video

Cited by 8 publications

References 9 publications

Augmented reality system to assist inexperienced pool players

Augmented reality system to assist inexperienced pool players

Visualizing multiple error-sensitivity fields for single camera positioning

Hierarchical Event Selection for Video Storyboards with a Case Study on Snooker Video Visualization

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