Abstract
This paper proposes a novel approach for visual features detection, which is based on the presence of objects whose shape can be modelled using cylinders or generalized cylinders. These specific structures are commonly found on indoor and outdoor scenarios, and their image representations, the so-called curvilinear regions, automatically deform with changing viewpoint as to keep on covering identical physical parts of a scene. The method is based on Marr's visual theory that proposes that visual objects can be decomposed in generalized cylinders. Also, part of the method can be compared to the behavior of AOS neurons, placed in the caudal intraparietal sulcus, that respond when an elongated object is visualized. Our detector reliably finds the same curvilinear regions under different viewing conditions. Evaluation results are given to demonstrate the performance of the approach and its ability to be applied for visual features detection in a mobile robot navigation framework.
Highlights
An autonomous robot must be capable of managing real situations in dynamic and complex environments and of interacting with people and/or other robots
The curvilinear regions that we propose have strong similarities with ribbons; the computation of the curvilinear properties that we propose is a novel approach
The proposed approach generates a reduced number of regions compared with maximally stable extremal region (MSER) and intensity extrema-based region detector (IBR) detectors (Figure 9(b))
Summary
An autonomous robot must be capable of managing real situations in dynamic and complex environments and of interacting with people and/or other robots. Feature-based navigation approaches mainly differ in the method employed to represent the belief of the mobile robot about its current pose or to find and track a safe path to a goal They can be differentiated according to the type of sensor information that they use. The biological inspiration for the choice of the visual features will allow to use regions with a high semantic significance for future applications The detection of these cylinders in the image could be considered the main disadvantage of the approach, as it depends on the presence of these specific structured landmarks in the scene. As it has been aforementioned, feature-based maps allow one to employ different models to describe the perceived environment.
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