Object Tracking Based on Kalman Filter for Catadioptric Omnidirectional Image
Maojun Zhang · Dianzi xuebao · 2011
Because of the features of catadioptric imaging,when the object has linear motion in real space,its trajectory on omnidirectional images is not a straight line,but conic.It leads to the big error in prediction of object's next position when applying trajectory prediction method for common perspective image.The authors adopt unifying catadioptric imaging sphere projection model to project object's imaging point in omnidirectional images onto the sphere where the author then establishes omnidirectional kalman filter to predict next position of the object.The result of prediction will project back to omnidirectional image to fulfill position prediction of objects.Experimental results in synthetic and real omnidirectional video demonstrate an obvious improvement in accuracy and stabilization of modified omnidirectional kalman filter in object position prediction.