Research Article
An Innovative SIFT-Based Method for Rigid Video Object Recognition
Algorithm 2
FModelUpdating(Output:
; Input:
,
,
(
),
//
to update feature models in with recognized frame image .
| (1) Calculate //to estimate the residual error which shows the degree of the similarity | | between the object feature models that and implying, denoted by and | | respectively | | (2) set //to set a lower limit to the degree of their similarity between | | and | | (3) if then | | (4) { | | (5) New(model(), ) //to create a new feature model in and save features in | | into it | | (6) Link(model(), model()) //to link to withall matching | | features between them | | (7) } | | (8) Else | | (9) { | | (10) Combine(model(), model()) //to combine with , which means | | the new features from should be added to the existing model | | (11) } | | (12) Endif | | (13) return |
|
