  In this paper, we propose mushrooms detection, localization and 3D pose
estimation algorithm using RGB-D data acquired from a low-cost consumer RGB-D
sensor. We use the RGB and depth information for different purposes. From RGB
color, we first extract initial contour locations of the mushrooms and then
provide both the initial contour locations and the original image to active
contour for mushrooms segmentation. These segmented mushrooms are then used as
input to a circular Hough transform for each mushroom detection including its
center and radius. Once each mushroom's center position in the RGB image is
known, we then use the depth information to locate it in 3D space i.e. in world
coordinate system. In case of missing depth information at the detected center
of each mushroom, we estimate from the nearest available depth information
within the radius of each mushroom. We also estimate the 3D pose of each
mushroom using a pre-prepared upright mushroom model. We use a global
registration followed by local refine registration approach for this 3D pose
estimation. From the estimated 3D pose, we use only the rotation part expressed
in quaternion as an orientation of each mushroom. These estimated (X,Y,Z)
positions, diameters and orientations of the mushrooms are used for
robotic-picking applications. We carry out extensive experiments on both 3D
printed and real mushrooms which show that our method has an interesting
performance.
