文档介绍：?????10246???061021071???????????????????????????Large Scale Moving Group Tracking and Three-dimensionalFace Pose Correction??????????????????????????????????????????2011?4????????????????????????????Large Scale Moving Group Tracking and Three-dimensional FacePose Correction???????????????????????????????????????????????????2011?4?AbstractCollective motion of large scale animal groups is one of the most spectacularscenes in the nature. Common examples include a ?ock of birds and a school ofswirling ?sh. Such phenomena have attracted great attention of many scientistsfor years. The most elaborate way to explore the underlying principles of collectivemotion would be through acquiring and quantitatively analyzing the motion dataof animal groups, while the rapid development of image acquisition devices anddigital image analysis methods allows us to puter vision techniques tomeasure the trajectory of each individual in a large is, however, very challenging to build such an automatic and -puter vision system due to: 1) collectively moving animal groups often involvein large numbers of individuals, and therefore occlusions will be very frequentin image sequences, which poses a very serious challenge for target detection andtracking; 2) individuals in a group often have similar visual features, and thereforethe existed object detection and matching algorithms which fully use the appear-ance feature would fail here. Motivated to address these challenges, this thesisproposed two methods for tracking large scale fruit ?y group ?ying in 3D spaceand ?sh school swimming in 2D shallow water, two video cameras capturing the moving groups in various views, theproposed method is implemented by solving three MAP (maximum a posterior)problems. The ?rst one is designed to track each individual in each video sequence,and is able to e?ciently maintain their identities in the presence of frequent occlu-sions; the second one is used to match the visually similar