Title :
Segmenting, Modeling, and Matching Video Clips Containing Multiple Moving Objects
Author :
Rothganger, Fred ; Lazebnik, Svetlana ; Schmid, Cordelia ; Ponce, Jean
Author_Institution :
Sandia Nat. Labs., Albuquerque, NM
fDate :
3/1/2007 12:00:00 AM
Abstract :
This paper presents a novel representation for dynamic scenes composed of multiple rigid objects that may undergo different motions and are observed by a moving camera. Multiview constraints associated with groups of affine-covariant scene patches and a normalized description of their appearance are used to segment a scene into its rigid components, construct three-dimensional models of these components, and match instances of models recovered from different image sequences. The proposed approach has been applied to the detection and matching of moving objects in video sequences and to shot matching, i.e., the identification of shots that depict the same scene in a video clip
Keywords :
image matching; image motion analysis; image segmentation; image sequences; video signal processing; image sequences; multiple moving objects; multiview constraints; video clips; video matching; video modeling; video segmentation; video sequences; Cameras; Computer vision; Content based retrieval; Gunshot detection systems; Image segmentation; Image sequences; Layout; Motion segmentation; Object detection; Video sequences; Affine-covariant patches; motion segmentation; shot matching; structure from motion; video retrieval.; Algorithms; Artificial Intelligence; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Models, Theoretical; Motion; Movement; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Subtraction Technique; Video Recording;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2007.57