This paper presents a method for localization of modeled objects that is general enough to cover articulated and other types of constrained models. The flexibility between components of the model are expressed as spatial constraints which are fused into the pose estimation process. The constraint fusion assists in obtaining a precise and stable pose of each object's component and in finding the correct interpretation. The proposed method can handle any constraint (including inequalities) between any number of different components of the model. The framework is based on Kalman filtering.
|Original language||American English|
|Title of host publication||Computer Vision — ECCV 1994 - 3rd European Conference on Computer Vision, Proceedings|
|Number of pages||12|
|State||Published - 1994|
|Event||3rd European Conference on Computer Vision, ECCV 1994 - Stockholm, Sweden|
Duration: 2 May 1994 → 6 May 1994
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||3rd European Conference on Computer Vision, ECCV 1994|
|Period||2/05/94 → 6/05/94|
Bibliographical notePublisher Copyright:
© Springer-Verlag Berlin Heidelberg 1994.