Biped Cartoon Retrieval Using LBG-Algorithm Based State Vector Quantization

Abstract

Efficiency of cartoon motion retrieval depends on indexing method. Keyword based indexing methods for restoring cartoon motion is simple, but sometimes the process of addressing index to the desired motion is not trivial. Although the methods based on clustering clips of motions or keyframes can be used for retrieval automatically, the complexity of time and reliability depend on size of the database. This research proposes a method for biped cartoon motion retrieval using state vectors of keyframes as the motion indexes. The state vectors derived from the input motion is quantized by our enhanced LBG Algorithm to compute the proper number of indexes for the set of input keyframes. The results show that not only the precision and recall of the cartoon motion retrieval is increased accurately but the process for restoring and retrieval is also performed automatically.