A Source Book Of Gestalt Psychology

By C. K. Ogden. 2013

248 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/946dffe06446c38a397fafb8d54e48c764196712

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In Clinical Psychology

Citations in the corpus

Bridging the Gap between Social Animal and Unsocial Machine: A Survey of Social Signal Processing (2012, unknown): “…(a pattern of physical energy) is received by an individual's sensory apparatus and then dynamically modeled through the effects of gestalt laws [47] becomes a percept: It is information, but information, in a sense, only similar to itself; if I see a " tree branch on the ground " I only know…”
The composite face illusion: A whole window into our understanding of holistic face perception (2013, unknown): “…law of Gestalt perception: The law of continuity, or good continuation, which states that oriented units/points tend to be integrated into perceptual wholes if they are connected or aligned with each other in straight or smoothly curving lines (Pomerantz & Kubovy, 1986; Wertheimer, 1925/1967).”
Consciousness as a phenomenon in the operational architectonics of brain organization: Criticality and self-organization considerations (2013, background): “complex patterns of qualities which are spatially extended and bounded with each other to form a unified item (Gestalt [79,80]) with a particular meaningful categorization (semantics [81]) immediately present for the subject.”
Cognitive Perspectives in Psychology (2013, background): “Thus, wholes are greater than the sum of their parts, and the nature of parts is determined by the wholes to which they belong (Wertheimer, 1924).”
A Century of Gestalt Psychology in Visual Perception I. Perceptual Grouping and Figure-Ground Organization (2012, methodology): “…of spatial and temporal factors in apparent motion was further investigated using the Ternus display (Kramer & Yantis, 1997; Pantle & Picciano, 1976; Ternus, 1926; Wallace & Scott- Samuel, 2007), in which an array of three dots is presented across two frames at different spatial locations.”
Deep clustering: Discriminative embeddings for segmentation and separation (2015, background): “First, of course, the assumed task of labeling known classes fundamentally does not address the general problem in real world signals that there may be a large number of possible classes, and many objects may not have a well-deﬁned class.”
Long-Term Image Boundary Prediction (2016, background): “Boundaries capture this crucial high frequency information and are also known to reveal important structures of the visual scene (Wertheimer 1923; Arbelaez et al. 2011; Galasso et al. 2013).”