Crop - CORSMAL Containers Manipulation (C-CCM)

Crop - CORSMAL Containers Manipulation (C-CCM) is a dataset for filling level classification from a single RGB image. C-CCM consists of 10,216 images automatically sampled, followed by manual verification, from public videos recordings of the CORSMAL Container Manipulation dataset.

C-CCM extracts RGB images using recordings from three fixed views, and capturing cups (4) and drinking glasses (4) as containers. The selected containers are red cup, small white cup, small transparent cup, green glass, wine glass, champagne flute, beer cup, and cocktail glass. Frames were also selected by considering that the object is completely visible or occluded by the person's hand, under different backgrounds, and for which the pouring process has been finalised (all frames where a person is still pouring the content were excluded). The containers can be transparent, translucent or opaque, while they can be empty or filled by a person (pouring) up to 50% or 90% of the capacity of the container with transparent (water) or opaque (pasta, rice) content.

C-CCM distributes selected RGB images, binary masks of the region with the container estimated using Mask R-CNN, and annotations of filling type and level, hand occlusion, transparency of the container, and rectangular bounding box indicating top-left and bottom-right corners for each image. Final images can be extracted again by cropping only the region with the container using the annotated bounding boxes. C-CCM provides a Python script to extract the image crops from the original images.