Stochasticks: Augmenting the Billiards Experience with Probabilistic Vision and Wearable Computers
ISWC '97 Proceedings of the 1st IEEE International Symposium on Wearable Computers
Performance evaluation of fuzzy-based decision system for pool
Applied Soft Computing
PickPocket: A computer billiards shark
Artificial Intelligence
AI Optimization of a Billiard Player
Journal of Intelligent and Robotic Systems
A computational model for developing semantic web-based educational systems
Knowledge-Based Systems
Billiards wizard: A tutoring system for broadcasting nine-ball billiards videos
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
On assisting a visual-facial affect recognition system with keyboard-stroke pattern information
Knowledge-Based Systems
A family of computer systems for delivering individualized advice
Knowledge-Based Systems
Aiming strategy error analysis and verification of a billiard training system
Knowledge-Based Systems
A novel image retrieval model based on the most relevant features
Knowledge-Based Systems
Journal of Intelligent and Robotic Systems
Hi-index | 0.00 |
Selecting the best sequence of shots for a given cue position is not an easy task in a game of billiards. The repositioning of the cue after its collision with an object ball determines its success on successive shots. A previous paper by the author was able to assist users in order to perfect a shot based on a selection criterion of maximum angle tolerance. This paper further extends the aiming capability to include a calculation of the ideal speed for the repositioning of the cue ball. The system makes use of a vision system for cue and object balls, and cue stick tracking. Users are able to adjust the cue stick in terms of both the aiming direction and hitting velocity according to the guidance information analyzed by a gaming strategy of this work. A new strategy is proposed to apply the maximum tolerance angle search sequentially twice. One on the pre-collision shot and the second on the post collision path. Additional to the maximum tolerance angle criterion, this paper also proposes a new visible object ball count criterion to assist cue ball repositioning strategy for both direct and indirect shots. This criterion was developed based on an analysis of the zero tolerance zone angle. It has been specifically tested to verify its relation with the successive sink rate using proposed guidance system. The experimental results of the maximum tolerance angle repositioning strategy of our training facility as tested by users with different skill levels all out performed the results without the advice for the same set of users. In addition, the distribution pattern of maximum tolerance test showed the highest degree of similarity with that of accessibility count as user skill level increases. This not only proves the reliability of our training system, but also proves the effectiveness of our algorithm for optimal repositioning.