Shape-based recognition of wiry objects

We present an approach to the recognition of complex-shaped objects in cluttered environments based on edge cues. We first use example images of the desired object in typical backgrounds to train a classifier cascade which determines whether edge pixels in an image belong to an instance of the object or the clutter. Presented with a novel image, we use the cascade to discard clutter edge pixels. The features used for this classification are localized, sparse edge density operations. Experiments validate the effective-ness of the technique for recognition of complex objects in cluttered indoor scenes under arbitrary out-of-image-plane rotation. 1 1