DYNAMIC SCENE ANALYSIS OF GROUP GAME

(1)群体行为的定性分析从群体关系的时间变迁角度分析足球比赛中的群体行为。游戏场景中的玩家群体被描述为直方图反向投影的分布。通过尺度空间滤波对分布映射进行平滑处理，并计算出群体层次的静态结构。我们将场景中的群体行为标注为群体层级的时间过渡。玩家动作的定性分析玩家的动作是通过检查X-Y-T空间中的奇异点从一系列图像中识别出来的。对球员的图像序列进行二值化处理，采用时间连续性保持细化算法检测出球员的三维骨架结构。动作的特征是基于骨架中的交叉点和分支来标注的。周期动作是通过图像间的时间相关性检测到的周期参数的变化来分割的。提出了一种基于active - netplayer的游戏场景玩家提取方法。该算法将Active-Net应用于直方图反向投影图像中，寻找多色实体的边界。直方图反向投影被调整为区分制服的颜色。我们还提出了一种自动参数调整方法来提高收敛速度，并提出了一种网状算法来精确提取形状。

(1). Qualitative analysis of group behaviorGroup behavior of soccer game is analyzed from temporal transition of group relation. Playr groups in the game scene are described as the distribution of by Histogram Backprojection. The distribution maps are smoothed by scale space filtering and a static structure of group hierarchy is computed. We annotated the group behavior in the scene as the temporal transition of group hierarchy.(2). Qualtative analysis of playr's actionThe action of a playr is identified from a sequence of image by examining singular points in X-Y-T space. Image sequence of a playr is binarized and the 3-D skeletal structure is detedted by temporal-continuity-preserving thinning algorithm. The characteristics of the action is annotated based on crossing points and branches in the skeleton. Periodical actions are segmented from the change of the periodicity parameter detected by temporal correlation between images.(3). Playr extraction by Active-NetPlayr extraction method from game scene has been developed. In the algorithm, the Active-Net is applied to Histogram Backprojection images to find the boundary of multi-colored entities. Histogram Backprojection is tuned up to descriminate the colors of uniforms. We have also proposed an automatic parameter adjustment method to emprove the speed to converge, and a net-tering algorthm for exact shape extraction.