Diagrams Based on Structured Object Perception

Most diagrams, particularly those used in software engineering, are line drawings consisting of nodes drawn as rectangles or circles, and edges drawn as lines linking them. In the present paper we review some of the literature on human perception to develop guidelines for effective diagram drawing. Particular attention is paid to structural object recognition theory. According to this theory as objects are perceived they are decomposed into 3D set of primitives called geons, together with the skeleton structure connecting them. We present a set of guidelines for drawing variations on node-link diagrams using geon-like primitives, and provide some examples. Results from three experiments are reported that evaluate 3D geon diagrams in comparison with 2D UML (Unified Modeling Language) diagrams. The first experiment measures the time and accuracy for a subject to recognize a sub-structure of a diagram represented either using geon primitives or UML primitives. The second and third experiments compare the accuracy of recalling geon vs. UML diagrams. The results of these experiments show that geon diagrams can be visually analyzed more rapidly, with fewer errors, and can be remembered better in comparison with equivalent UML diagrams

Exploring Object Perception with Random Image Structure Evolution

We have developed a technique called RISE (Random Image Structure Evolution), by which one may systematically sample continuous paths in a high-dimensional image space. A basic RISE sequence depicts the evolution of an object's image from a random field, along with the reverse sequence which depicts the transformation of this image back into randomness. The processing steps are designed to ensure that important low-level image attributes such as the frequency spectrum and luminance are held constant throughout a RISE sequence. Experiments based on the RISE paradigm can be used to address some key open issues in object perception. These include determining the neural substrates underlying object perception, the role of prior knowledge and expectation in object perception, and the developmental changes in object perception skills from infancy to adulthood

Bodily self-awareness and object perception

In this paper I would like to argue that proprioceptive awareness (including both somatic and ecological proprioception) is primarily a form of non-perceptual awareness. This might seem to be an obscure point, but it turns out to be philosophically significant in regard to what Shoemaker calls ‘immunity to error through misidentification’. Although it is possible to make a mistake in identifying one’s body via sense-perceptual modalities such as vision, some philosophers argue that one is immune to error through misidentification in regard to knowing one’s own body by means of proprioception (Cassam, 1995; Evans, 1982). If proprioception were a form of perception then it would be possible for one to proprioceptively misidentify oneself in referring to one’s body. In arguing that proprioception is not a form of perception I am defending the immunity principle in this regard

Modeling infant object perception as program induction

Infants expect physical objects to be rigid and persist through space and time and in spite of occlusion. Developmentists frequently attribute these expectations to a "core system" for object recognition. However, it is unclear if this move is necessary. If object representations emerge reliably from general inductive learning mechanisms exposed to small amounts of environment data, it could be that infants simply induce these assumptions very early. Here, we demonstrate that a domain general learning system, previously used to model concept learning and language learning, can also induce models of these distinctive "core" properties of objects after exposure to a small number of examples. Across eight micro-worlds inspired by experiments from the developmental literature, our model generates concepts that capture core object properties, including rigidity and object persistence. Our findings suggest infant object perception may rely on a general cognitive process that creates models to maximize the likelihood of observationsComment: 3 pages, 3 figures, accepted at CCN conference 202