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Please consider the following excerpt (from Rodrigo R, Zouqi M, Chen Z, Samarabandu J.: Robust and efficient feature tracking for indoor navigation):

Robust feature tracking is a requirement for many computer vision tasks such as indoor robot navigation. However, indoor scenes are characterized by poorly localizable features.

I am trying to understand what localizability is, and would appreciate help. (PS: I know there is a dsp tag called "local-features", but the tag currently has no definition.)

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In the robot navigation problem, the localization problem refers to the real time estimation of its position and orientation under various backgrounds. This is usually achieved by some natural landmark selection (laser points, camera views, etc.), and the features in the image (corners, tiny lines with different orientations, etc.). So the localizability reflects how easy, robust and consistent the robot's position and orientation can be estimated with the choice of feature points.

Hugues Sert et al's Mobile robot algebraic localizability includes more strict definition with details, and its relation to observability.

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