Due to the condition imposed for a pixel to remain classified as static in a long-term basis, the system can be interactively corrected by an operator without need for the system to modify anything in the background models, what alleviates the system from persistent false classification originated by incorrect update decisions in contrast to selective updating-based systems.
However, occlusion events and clutter may affect the model learning, leading to a distraction in the estimation of the new position of the target as well as incorrect updating of the shape model.
The disadvantage of this approach is that incorrect update decisions might later result in incorrect detection and that the uncovered background could be detected as foreground after removing static objects even if those do not get absorbed by the long-term model if the lighting conditions have changed notably.
Recently, Singh et al. [4] proposed a system for the detection of static objects that also bases on two background models however; it relies on selectively updating the long-term background model, entailing the above-mentioned problem of possibly taking incorrect updating decisions, and on tracking information.
Owing to the same reason, Das further showed that the scheme suffers from incorrect password updating problem.
Take these typical elements: Nonlinear narrative, multimedia, abstraction, fractured language, fourth-wall breaking, colorblind casting, stylized acting, drama-interrupting dance, site-specific settings, confessional performance art, politically incorrect provocation, irreverent updating or deconstruction of classic texts, mixing of high and low culture.
Incorrect background model updating tends to introduce incorrect models because of motion ambiguities.
In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data.
Approximately 7% of these (n=287) were returned because the address was incorrect, and no updated address could be found through publicly available sources.
