Paper Info
Title
SketchIt: basketball video retrieval using ball motion similarity
Abstract
A prototype basketball video retrieval system is presented in this paper. Retrieval is based on the similarity of ball motion in the clip with that in the query. The system uses a query-by-sketch paradigm, where the user provides a sketch of the desired ball trajectory. The video data is pre-processed to make the ball motion invariant to camera translation. The next stage is dimensionality reduction wherein we model the ball motion as a set of parabolic trajectories. An R-tree is used to index these parabolic representations and search for similar trajectories in a low dimension parametric space. The query is processed to obtain its parametric representation, and a nearest neighbor search is performed for similar parabolas. These query results are then post-processed by assigning scores based on various similarity criteria. The system could be extended to other types of videos and moving objects. As a proof of concept, the system was tested for ball trajectories in basketball video.
Year
DOI
Venue
2004
10.1007/978-3-540-30542-2_32
PCM (2)
Keywords
Field
DocType
ball motion invariant,nearest neighbor search,ball motion,video data,query result,parabolic representation,ball motion similarity,low dimension parametric space,prototype basketball video retrieval,ball trajectory,basketball video,indexation,proof of concept
Computer vision,Dimensionality reduction,Pattern recognition,Computer science,Parametric statistics,Invariant (mathematics),Artificial intelligence,Nearest neighbor search,Trajectory,Parabola,Sketch,Basketball
Conference
Volume
ISSN
ISBN
3332
0302-9743
3-540-23977-4
Citations 
PageRank 
References 
3
0.42
12
Authors
2
Name
Order
Citations
PageRank
Sitaram Bhagavathy11149.82
Motaz El-Saban235018.45