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Dipl.-Ing. Dr. Benedikt Gollan

Operativer Studioleiter

Dr. Benedikt Gollan absolvierte das Studium der Elektro- & Informationstechnik an der Technischen Universität München (TUM) und ist seit April 2010 als wissenschaftlicher Mitarbeiter im Studio Pervasive Computing Applications (PCA) am Standort in Wien tätig. Seine Dissertation "Sensor-based Online Assessment of Human Attention" schloß er 2018 an der JKU Linz ab.

Den fachlichen Schwerpunkt seiner Arbeit bildet die automatische Merkmalserkennung in diversen Bereichen (Audio/Video, diverse Formen der expliziten und impliziten Interaktion). Insbesondere beschäftigt er sich mit der technischen Erfassung kognitiver Zustände (menschliche Aufmerksamkeit) und deren Rolle in der Interaktion mit technischen Informationssystemen (Attention-Aware ICT).

Aktuelle Projekte:

Attentive ICT, Projekt zur industrienahen Dissertationsförderung, FFG
Im Rahmen des Attentive ICT Projektes wird die Dissertation von DI Benedikt Gollan gefördert. Inhalt ist die Erforschung der technischen Erfassung von Aufmerksamkeit mittels sensorischer Analyse von beobachtbaren Aufmerksamkeitsindikatoren.

Raising Attention, Sondierungsprojekt IKT der Zukunft, FFG
Mobilisierung einer nationalen Forschungsinitiative im Bereich Attention-Aware ICT, Durchführung von Veranstaltungen, Ausarbeitung eines Whitebooks inklusive Forschungs-Roadmap.
http://www.raising-attention.org/

360Light, Bridge Projekt, FFG
Entwicklung einer intuitiven Gesteninteraktion für panoramische Inhalte in Multi-Display Installationen
http://pervasive.researchstudio.at/360-light

 

Publikationen:

Gollan, B., Haslgrübler, M., & Ferscha, A. 
"Demonstrator for extracting cognitive load from pupil dilation for attention management services". In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (pp. 1566-1571). ACM.(2016, September).

Abstract:
Attention Management has become a fundamental requirement in interaction design of information systems, considering the information overload distributed by omnipresent wearable devices. This implies the management of notifications and interruptions according to current user activities, context and especially cognitive load and perception capabilities. This paper presents a demonstrator designed towards the real-time assessment of cognitive load from pupil dilation as a somatic indicator of attention, which can be exploited as input for the control of future attention-aware interaction designs. Cognitive Load is modeled from pupil dilation via exploiting the task-evoked pupil response while considering disturbances of illumination and blink activities.

Gollan, B., & Ferscha, A.
"Modeling Pupil Dilation as Online Input for Estimation of Cognitive Load in non-laboratory Attention-Aware Systems." In 
COGNITIVE 2016-The Eighth International Conference on Advanced Cognitive Technologies and Applications(2016). 

Abstract:
Dynamic changes of pupil dilation represent an established indicator of cognitive load in cognitive sciences Exploitation of these insights regarding pupil dilation as an indicator of cognitive load for attention-aware Information and Communication (ICT) systems has been impeded due to restrictions of pupil analysis to a posteriori processing and exclusion of disturbing environmental factors. To overcome these issues, this paper proposes an algorithm based on Hoeks’s pupil response model, enabling online analysis of pupil dilation for the dynamic interpretation of cognitive load as an input for interactive, attention-aware systems, which outperforms state-of-the-art approaches regarding complexity, accuracy, flexibility and computation time. Beyond mathematical pupil modeling, this paper identifies Environment Illumination compensation (IC), Blink Compensation (BC), Reference Baseline computation (RB) and Onset/Offset detection (OO) as crucial fields of research for the transfer of pupillometry from the laboratory into real-life application scenarios.

Ferscha, A., Zia, K., & Gollan, B. 
"Collective attention through public displays". In Self-Adaptive and Self-Organizing Systems (SASO), 2012 IEEE Sixth International Conference on (pp. 211-216). IEEE. (2012, September)

Abstract:
The dynamics of collective attention emerging out of individual viewing experiences from public displays appear to be among the most demanding challenges in understanding the mechanisms of self-adaptation of public opinion. In this paper we approach a model of collective attention from observations of the attention of individuals estimated from their efforts expressing interest. Extending on SEEV, an established individual attention model from cognitive science, attention estimates from spontaneous passer-bys in front of public displays are used to describe a collective attention model at the scale of society. The model is validated via a large scale simulation experiment reflecting the demographics and the morphology of a whole city, together with population densities, mobility patterns and individual decision making on a 2048 node shared memory multiprocessor (SGI Altix Ultra Violet 1000, Repast HPC). Simulations how collective attention emerges from local spots of attention towards city scale opinion building and consensus finding.

Benedikt Gollan, Alois Ferscha,
„A Generic Effort-Based Behavior Description for User Engagement Analysis”, IEEE Lecture Notes in Computer Science 8908, PhyCS 2014

Abstract:
Human interaction is to a large extent based on implicit, unconscious behavior and the related body language. In this article, we propose ‘Directed Effort’ a generic description of human behavior suitable as user engagement and interest input for higher level human-computer interaction applications. Research from behavioral and psychological sciences is consulted for the creation of an attention model which is designed to represent the engagement of people towards generic objects in public spaces. The functionality of this behavior analysis approach is demonstrated in a prototypical implementation to present the potential of the presented meta-level description of behavior.

 

Ferscha, Alois, Kashif Zia, and Benedikt Gollan.
"Collective Attention through Public Displays." Self-Adaptive and Self-Organizing Systems (SASO), 2012 IEEE Sixth International Conference on. IEEE, 2012.

Abstract:

The dynamics of collective attention emerging out of individual viewing experiences from public displays appear to be among the most demanding challenges in understanding the mechanisms of self-adaptation of public opinion. In this paper we approach a model of collective attention from observations of the attention of individuals estimated from their efforts expressing interest. Extending on SEEV, an established individual attention model from cognitive science, attention estimates from spontaneous passer-bys in front of public displays are used to describe a collective attention model at the scale of society. The model is validated via a large scale simulation experiment reflecting the demographics and the morphology of a whole city, together with population densities, mobility patterns and individual decision making on a 2048 node shared memory multiprocessor (SGI Altix Ultra Violet 1000, Repast HPC). Simulations how collective attention emerges from local spots of attention towards city scale opinion building and consensus finding.

 

Schuller, Björn, and Benedikt Gollan.
"Music theoretic and perception-based features for audio key determination." Journal of New Music Research 41.2 (2012): 175-193.

Gollan, Benedikt, Bernhard Wally, and Alois Ferscha.
"Automatic Human Attention Estimation in an Interactive System based on Behaviour Analysis."Proc. EPIA 2011 (2011).

Abstract:

The dynamics of collective attention emerging out of individual viewing experiences from public displays appear to be among the most demanding challenges in understanding the mechanisms of self-adaptation of public opinion. In this paper we approach a model of collective attention from observations of the attention of individuals estimated from their efforts expressing interest. Extending on SEEV, an established individual attention model from cognitive science, attention estimates from spontaneous passer-bys in front of public displays are used to describe a collective attention model at the scale of society. The model is validated via a large scale simulation experiment reflecting the demographics and the morphology of a whole city, together with population densities, mobility patterns and individual decision making on a 2048 node shared memory multiprocessor (SGI Altix Ultra Violet 1000, Repast HPC). Simulations how collective attention emerges from local spots of attention towards city scale opinion building and consensus finding.

 

Gollan, Benedikt, Bernhard Wally, and Alois Ferscha.
"ID Management Strategies for Interactive Systems in Multi-Camera Scenarios." Vehicular Technology Conference (VTC Spring), 2011 IEEE 73rd. IEEE, 2011.

 

Projekte:

Attend2IT
Attentive ICT
Attentive Machines
EyeControl
Raising Attention
FuturICT
PowerIT
Interactive Displays
Displays http://www.pervasive.jku.at/Research/Projects/?key=1022

 

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