Recognizing solid objects by alignment with an image
International Journal of Computer Vision
3-D Shape Recovery Using Distributed Aspect Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
From volumes to views: an approach to 3-D object recognition
CVGIP: Image Understanding - Special issue on directions in CAD-based vision
Shock Graphs and Shape Matching
International Journal of Computer Vision
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual Organization and Visual Recognition
Perceptual Organization and Visual Recognition
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
TurboPixels: Fast Superpixels Using Geometric Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-time scale selection in hybrid multi-scale representations
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Optimal contour closure by superpixel grouping
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Edge Grouping Combining Boundary and Region Information
IEEE Transactions on Image Processing
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Perceptual grouping plays a critical role in both human and computer vision. However, with the object categorization community's preoccupation with object detection, interest in perceptual grouping has waned. The reason for this is clear: the object-independent, mid-level shape priors that form the basis of perceptual grouping are subsumed by the object-dependent, high-level shape priors defined by a target object. As the recognition community moves from object detection back to object recognition, a linear search through a large database of target models is intractable, and perceptual grouping will be essential for sublinear scaling. We review two approaches to perceptual grouping based on grouping superpixels. In the first, we use symmetry to group superpixels into symmetric parts, and then group the parts to form structured objects. In the second, we use contour closure to group superpixels, yielding a figure-ground segmentation.