Understanding the Importance of Different Edge Types in Image Recognition
This content delves into the significance of various edge types in image recognition, exploring the impact of edges such as albedo, depth, surface normal, and shadow on the recognition process. Researchers have studied the effects of different edge types through works dating back to the 1960s, aiming to isolate their specific contributions. Synthetic scenes have been utilized to analyze edges' roles in different visual contexts, shedding light on their implications for image processing and scene understanding.
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Presentation Transcript
Which edges matter? Aayush Bansal (CMU), Adarsh Kowdle (Microsoft), Devi Parikh (VT), Andrew Gallagher (Cornell), Larry Zitnick (MSR)
Edge types Albedo Depth Surface normal Shadow
Can we isolate the effect of different edge types?
Synthetic scenes 46 scenes, Google 3DWarehouse
Synthetic scenes Black and white
Synthetic scenes Albedo
Synthetic scenes Gray surface
Synthetic scenes Gray shaded
Synthetic scenes Depth
Edges RGB Albedo Depth Gray surface Gray shaded
Human studies 265 objects, 11 scene types, 10 subjects per test
What type of edges do our edge detectors find?
Precision Depth Surface normal Shadow Texture
Recall Depth Surface normal Shadow Texture
Can we further improve our edge detectors?
Contour detection Parikh and Zitnick, CVPR 2012
Conclusion Depth and surface normal edges are most informative for recognition Most automatic edge detectors find a significant number of albedo and shadow edges Better methods for evaluating edge detectors? Are lines important or just edges?
