The Strange Nature of Quantum Perception: To See a Photon, One Must _Be_ a Photon

This paper takes as its point of departure recent research into the possibility that human beings can perceive single photons. In order to appreciate what quantum perception may entail, we first explore several of the leading interpretations of quantum mechanics, then consider an alternative view based on the ontological phenomenology of Maurice Merleau-Ponty and Martin Heidegger. Next, the philosophical analysis is brought into sharper focus by employing a perceptual model, the Necker cube, augmented by the topology of the Klein bottle. This paves the way for addressing in greater depth the paper’s central question: Just what would it take to observe the quantum reality of the photon? In formulating an answer, we examine the nature of scientific objectivity itself, along with the paradoxical properties of light. The conclusion reached is that quantum perception requires a new kind of observation, one in which the observer of the photon adopts a concretely self-reflexive observational posture that brings her into close ontological relationship with the observed

Subjectively interpreted shape dimensions as privileged and orthogonal axes in mental shape space

The shape of an object is fundamental in object recognition but it is still an open issue to what extent shape differences are perceived analytically (i.e., by the dimensional structure of the shapes) or holistically (i.e., by the overall similarity of the shapes). The dimensional structure of a stimulus is available in a primary stage of processing for separable dimensions, although it can also be derived cognitively from a perceived stimulus consisting of integral dimensions. Contrary to most experimental paradigms, the present study asked participants explicitly to analyze shapes according to two dimensions. The dimensions of interest were aspect ratio and medial axis curvature, and a new procedure was used to measure the participants' interpretation of both dimensions (Part I, Experiment 1). The subjectively interpreted shape dimensions showed specific characteristics supporting the conclusion that they also constitute perceptual dimensions with objective behavioral characteristics (Part II): (1) the dimensions did not correlate in overall similarity measures (Experiment 2), (2) they were more separable in a speeded categorization task (Experiment 3), and (3) they were invariant across different complex 2-D shapes (Experiment 4). The implications of these findings for shape-based object processing are discussed

Real-time Spatial Detection and Tracking of Resources in a Construction Environment

Construction accidents with heavy equipment and bad decision making can be based on poor knowledge of the site environment and in both cases may lead to work interruptions and costly delays. Supporting the construction environment with real-time generated three-dimensional (3D) models can help preventing accidents as well as support management by modeling infrastructure assets in 3D. Such models can be integrated in the path planning of construction equipment operations for obstacle avoidance or in a 4D model that simulates construction processes. Detecting and guiding resources, such as personnel, machines and materials in and to the right place on time requires methods and technologies supplying information in real-time. This paper presents research in real-time 3D laser scanning and modeling using high range frame update rate scanning technology. Existing and emerging sensors and techniques in three-dimensional modeling are explained. The presented research successfully developed computational models and algorithms for the real-time detection, tracking, and three-dimensional modeling of static and dynamic construction resources, such as workforce, machines, equipment, and materials based on a 3D video range camera. In particular, the proposed algorithm for rapidly modeling three-dimensional scenes is explained. Laboratory and outdoor field experiments that were conducted to validate the algorithm’s performance and results are discussed

Elastic membrane based model of human perception

In this work a new approach to multidimensional geometry and multidimensional physics based on smooth infinitesimal analysis (SIA) is proposed. Reality may be considered as the process of time evolution of holistic energetically very weak macro objects - elastic membranes with the geometry based on smooth infinitesimal analysis. An embedded membrane in this multidimensional world will look different for the external and internal observers: from the outside it will look like a material object with smooth infinitesimal geometry, while from the inside our Universe-like space-time fabric. It is shown that our perception may be considered as the result of elastic oscillations of two dimensional elastic membranes with closed topology embedded in our bodies. Only one elastic membrane responsible for its perceptions will correspond to the selected organism, but there may be other membranes, even at the cell level. Elastic membranes stretch and propagate along the direction of attentive focus and occupy energetically favorable positions around microtubules involved into ORch OR. According to the model ORch OR and the elastic membrane corresponding to the living organism are closely connected and support each other

Socially extending the mind through social affordances

The extended mind thesis claims that at least some cognitive processes extend beyond the organism’s brain in that they are constituted by the organism’s actions on its surrounding environment. A more radical move would be to claim that social actions performed by the organism could at least constitute some of its mental processes. This can be called the socially extended mind thesis. Based on the notion of affordance as developed in the ecological psychology tradition, I defend the position that perception extends to the environment. Then I will expand the notion of affordance to encompass social affordances. Thus, perception can in some situations also be socially extended

Motion sequence analysis in the presence of figural cues

Published in final edited form as: Neurocomputing. 2015 January 5, 147: 485–491The perception of 3-D structure in dynamic sequences is believed to be subserved primarily through the use of motion cues. However, real-world sequences contain many figural shape cues besides the dynamic ones. We hypothesize that if figural cues are perceptually significant during sequence analysis, then inconsistencies in these cues over time would lead to percepts of non-rigidity in sequences showing physically rigid objects in motion. We develop an experimental paradigm to test this hypothesis and present results with two patients with impairments in motion perception due to focal neurological damage, as well as two control subjects. Consistent with our hypothesis, the data suggest that figural cues strongly influence the perception of structure in motion sequences, even to the extent of inducing non-rigid percepts in sequences where motion information alone would yield rigid structures. Beyond helping to probe the issue of shape perception, our experimental paradigm might also serve as a possible perceptual assessment tool in a clinical setting.The authors wish to thank all observers who participated in the experiments reported here. This research and the preparation of this manuscript was supported by the National Institutes of Health RO1 NS064100 grant to LMV. (RO1 NS064100 - National Institutes of Health)Accepted manuscrip

Identification of Invariant Sensorimotor Structures as a Prerequisite for the Discovery of Objects

Perceiving the surrounding environment in terms of objects is useful for any general purpose intelligent agent. In this paper, we investigate a fundamental mechanism making object perception possible, namely the identification of spatio-temporally invariant structures in the sensorimotor experience of an agent. We take inspiration from the Sensorimotor Contingencies Theory to define a computational model of this mechanism through a sensorimotor, unsupervised and predictive approach. Our model is based on processing the unsupervised interaction of an artificial agent with its environment. We show how spatio-temporally invariant structures in the environment induce regularities in the sensorimotor experience of an agent, and how this agent, while building a predictive model of its sensorimotor experience, can capture them as densely connected subgraphs in a graph of sensory states connected by motor commands. Our approach is focused on elementary mechanisms, and is illustrated with a set of simple experiments in which an agent interacts with an environment. We show how the agent can build an internal model of moving but spatio-temporally invariant structures by performing a Spectral Clustering of the graph modeling its overall sensorimotor experiences. We systematically examine properties of the model, shedding light more globally on the specificities of the paradigm with respect to methods based on the supervised processing of collections of static images.Comment: 24 pages, 10 figures, published in Frontiers Robotics and A