There are many situations where using a depth camera as input into a machine learning system can offer additional benefits and features – as we previously discussed in a prior blog post “What does Depth Bring to Machine Learning.” Depth cameras have a number of advantages for a variety of machine learning problems, including lighting invariance. Depth cameras can easily adapt to a wide variety of lighting conditions, something that 2D models must be trained to compensate for. A depth camera also allows differentiation between items of different size as well as easier background segmentation, allowing the separation of individual items regardless of how complicated the background is.
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