Logo des Repositoriums

Auflistung nach Autor:in "Neumann, Heiko"

1 - 2 von 2
  • Zeitschriftenartikel
    Beyond Simple and Complex Neurons: Towards Intermediate-level Representations of Shapes and Objects
    (KI - Künstliche Intelligenz: Vol. 29, No. 1, 2015) Rodríguez-Sánchez, Antonio; Neumann, Heiko; Piater, Justus
    Knowledge of the brain has much advanced since the concept of the neuron doctrine developed by Ramón y Cajal (R Trim Histol Norm Patol 1:33–49, 1888). Over the last six decades a wide range of functionalities of neurons in the visual cortex have been identified. These neurons can be hierarchically organized into areas since neurons cluster according to structural properties and related function. The neurons in such areas can be characterized to a first order approximation by their (static) receptive field function, viz their filter characteristic implemented by their connection weights to neighboring cells. This paper aims to provide insights on the steps that computer models in our opinion must pursue in order to develop robust recognition mechanisms that mimic biological processing capabilities beyond the level of cells with classical simple and complex receptive field response properties. We stress the importance of intermediate-level representations to achieve higher-level object abstraction in the context of feature representations, and summarize two current approaches that we consider are advances toward achieving that goal.
  • Konferenzbeitrag
    Social Signal Processing in Companion Systems - Challenges Ahead
    (INFORMATIK 2011 – Informatik schafft Communities, 2011) Layher, Georg; Tschechne, Stephan; Scherer, Stefan; Brosch, Tobias; Curio, Cristóbal; Neumann, Heiko
    Companion technologies aim at developing sustained long-term relationships by employing emotional, nonverbal communication skills and empathy. One of the main challenges is to equip such companions with human-like abilities to reliably detect and analyze social signals. In this proposal, we focus our investigation on the modeling of visual processing mechanisms, since evidence in literature suggests that nonverbal interaction plays a key role in steering, controlling and maintaining social interaction between humans. We seek to transfer fragments of this competence to the domain of human computer interaction. Some core computational mechanisms of extracting and analyzing nonverbal signals are presented, enabling virtual agents to create socially competent response behaviors.