Title :
Moving object detection and trajectory estimation in the transform/spatiotemporal mixed domain
Author :
Knudsen, K.S. ; Bruton, L.T.
Author_Institution :
Dept. of Electr. & Comput Eng., Calgary Univ., Alta., Canada
Abstract :
A novel discrete transform/spatiotemporal mixed domain, or MixeD, moving object detection and trajectory estimation algorithm is introduced. It is known that the energy of a linear trajectory moving object is confined to a plane in the 3-D frequency domain. The 2-D discrete Fourier transform (DFT) is combined with a 1-D high-resolution spectral estimation method to identify and locate the plane, and thereby estimate the object´s trajectory. An example is provided to demonstrate that the MixeD moving object detection and trajectory estimation algorithm is able to discriminate several moving objects in an image sequence, and to provide accurate estimates of their trajectories
Keywords :
fast Fourier transforms; filtering and prediction theory; image sequences; motion estimation; tracking; 1-D high-resolution spectral estimation; 2-D discrete Fourier transform; 3-D frequency domain; DFT; MixeD; forward-backward linear prediction; image sequence; linear trajectory; moving object detection; trajectory estimation; transform/spatiotemporal mixed domain; Aircraft navigation; Discrete Fourier transforms; Frequency domain analysis; Frequency estimation; Image sequences; Land vehicles; Multidimensional signal processing; Object detection; Signal processing; Spatiotemporal phenomena;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0532-9
DOI :
10.1109/ICASSP.1992.226165