Animate vision systems have gaze control mechanisms that can actively position the camera coordinate system in response to physical stimuli. Compared to passive systems, animate systems show that visual computation can be vastly less expensive when considered in the larger context of behavior. The most important visual behavior is the ability to control the direction of gaze. This allows the use of very low resolution imaging that has a high virtual resolution. Using such a system in a controlled way provides (...) additional constraints that dramatically simplify the computations of early vision. Another important behavior is the way the environment “behaves‘. Animate systems under real-time constraints can further reduce their computational burden by using environmental cues that are perspicuous in the local context. A third source of economy is introduced when behaviors are learned. Because errors are rarely fatal, systems using learning algorithms can amortize computational cost over extended periods. Further economies can be achieved when the learning system uses indexical reference, which is a form of dynamic variable binding. Animate vision is a natural way of implementing this dynamic binding. (shrink)

People coordinate body postures and gaze patterns during conversation. We review literature showing that (1) action embodies cognition, (2) postural coordination emerges spontaneously when two people converse, (3) gaze patterns influence postural coordination, (4) gaze coordination is a function of common ground knowledge and visual information that conversants believe they share, and (5) gaze coordination is causally related to mutual understanding. We then consider how coordination, generally, can be understood as temporarily coupled neuromuscular components that function as a collective unit (...) known as a coordinative structure in the motor control literature. We speculate that the coordination of gaze and body sway found in conversation may be understood as a cross‐person coordinative structure that embodies the goals of the joint action system. (shrink)

Conversation is supported by the beliefs that people have in common and the perceptual experience that they share. The visual context of a conversation has two aspects: the information that is available to each conversant, and their beliefs about what is present for each other. In our experiment, we separated these factors for the first time and examined their impact on a spontaneous conversation. We manipulated the fact that a visual scene was shared or not and the belief that a (...) visual scene was shared or not. Participants watched videos of actors talking about a controversial topic, then discussed their own views while looking at either a blank screen or the actors. Each believed (correctly or not) that their partner was either looking at a blank screen or the same images. We recorded conversants’ eye movements, quantified how they were coordinated, and analyzed their speech patterns. Gaze coordination has been shown to be causally related to the knowledge people share before a conversation, and the information they later recall. Here, we found that both the presence of the visual scene, and beliefs about its presence for another, influenced language use and gaze coordination. (shrink)

The pull to coordinate with other individuals is fundamental, serving as the basis for our social connectedness to others. Discussed is a dynamical and ecological perspective to joint action, an approach that embeds the individual’s mind in a body and the body in a niche, a physical and social environment. Research on uninstructed coordination of simple incidental rhythmic movement, along with research on goal‐directed, embodied cooperation, is reviewed. Finally, recent research is discussed that extends the coordination and cooperation studies, examining (...) how synchronizing with another, and how emergent social units of perceiving and acting are reflected in people’s feelings of connection to others. (shrink)

The visual world of adults consists of objects at various distances, partly occluding one another, substantial and stable across space and time. The visual world of young infants, in contrast, is often fragmented and unstable, consisting not of coherent objects but rather surfaces that move in unpredictable ways. Evidence from computational modeling and from experiments with human infants highlights three kinds of learning that contribute to infants’ knowledge of the visual world: learning via association, learning via active assembly, and learning (...) via visual-manual exploration. Infants acquire knowledge by observing objects move in and out of sight, forming associations of these different views. In addition, the infant’s own self-produced behavior—oculomotor patterns and manual experience, in particular—is an important means by which infants discover and construct their visual world. (shrink)