A visual attention network for a humanoid robot

From Robot Arm to Intentional Agent: the Articulated Head

“…One of the first implementations, named FeatureGate, used an artificial neural network that operated on 2D feature maps (Driscoll et al, 1998), specifically -in the tests presented in the paper -feature maps derived from synthetic images. In its handling of how the features were weighted, it allowed changes depending on the task, that is, top-down attention was partially established.…”

The new robotics—towards human‐centered machines

“…Visual attention with robot vision heads has also been explored extensively (e.g., Braun, 1994;Driscoll et al, 1998;Breazeal et al, 2001;Shibata et al, 2001;), but it is just recently that a rather comprehensive visual attention system for technical applications was derived from insight from neurobiology (Koch and Ullman, 1985;Itti and Koch, 2000a;Itti and Koch, 2000b;Itti and Koch, 2001;Itti et al, 2003). This work is currently on its way to explore how intention (i.e., top-down task relevant biases) can influence attention and decision making (Navalpakkam and Itti, 2005;Carmi and Itti, 2006).…”

Visual Attention and Distributed Processing of Visual Information for the Control of Humanoid Robots

“…The input to the motor system is the desired eye position, which is continuously compared to an efference copy of the internal representation of the eye position. Many computational models of preattentive processing have been influenced by the feature integration theory (Treisman and Gelade, 1980), which resulted in several technical implementations, e. g. (Itti et al, 1998), including some implementations on humanoid robots (Driscoll et al, 1998;Breazeal and Scasselatti, 1999;Stasse et al, 2000;Vijayakumar et , 2001). With the exception of (Driscoll et al, 1998), these implementations are mainly concerned with bottom-up, data-driven processing directed towards the generation of saliency maps.…”

“…Many computational models of preattentive processing have been influenced by the feature integration theory (Treisman and Gelade, 1980), which resulted in several technical implementations, e. g. (Itti et al, 1998), including some implementations on humanoid robots (Driscoll et al, 1998;Breazeal and Scasselatti, 1999;Stasse et al, 2000;Vijayakumar et , 2001). With the exception of (Driscoll et al, 1998), these implementations are mainly concerned with bottom-up, data-driven processing directed towards the generation of saliency maps. However, many theories of visual search, e. g. guided search, suggests that there are several ways for preattentive processing to guide the deployment of attention (Wolfe, 2003).…”