基于姿势特征编码的运动数据分层检索

运动数据检索是为在已有的运动数据库中检索符合要求的数据进行重用和编辑, 基于姿势特征编码的分 层检索方式能提高检索速度和检索质量。 通过对运动骨骼分段, 提取能反应几何运动关系的骨骼分段夹角作 为特征向量, 对姿势特征进行编码, 建立基于运动特征的数据库索引, 并在检索过程中分别从运动特征、 数据索引和运动数值进行相似度比较。 实验结果表明, 在具有走、 跑、 舞等姿态的运动数据库中, 该方法相对 于其他方法具有较高的检索速度, 并得到满意的检索结果, 实现了运动逻辑相似性的有效检索。

Motion Data Hierarchical Retrieval Based on Pose Feature Coding

Motion data retrieval is used to get the proper data from the existing motion database for motion editing and reusing, the hierarchical retrieval based on posture feature coding improves the retrieval speed and quality. We divide major bone into nine segments, and the angles of these bone segments can response geometric relations of motion posture, can used as feature vectors, encode posture features, create database index based on the motion features, in the retrieval process, carry out the similarity comparison from motion feature, data index and motion data value. The experimental results shows, in the motion database that contains walk, run and dance postures, compared with the other method, the method has high retrieval speed and satisfactory retrieval results, and realize the effectively retrieve of the logical similarity motion data.