View-Invariant Recognition Using Corresponding Object Fragments

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View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation (2016, positive): “Several hierarchical models of object recognition [17, 40, 43, 9] and face recognition [8, 29, 14] feature a progression from view-specific early processing stages to view-invariant later processing stages similar to ML/MF and AM, respectively.”
Class-Based Feature Matching Across Unrestricted Transformations (2008, unknown): “In [19], matching regions were learned from video sequences.”
A stochastic graph grammar for compositional object representation and recognition (2009, background): “This field, which gained prominence in the 1990s with holistic appearance models [9], later grew to include local representations using invariant feature points [10], patches [6] and fragments [11].”
Groups of Adjacent Contour Segments for Object Detection (2008, background): “is the average strength of its edgels Ps ∈ [0, 1].”
Evaluating Appearance Models for Recognition, Reacquisition, and Tracking (2007, background): “These features could be simple Haar like features [20], complex image patches[1] [10] or SIFT features [21].”