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ICARCV
2008
IEEE
138views Robotics» more  ICARCV 2008»
15 years 10 months ago
Looking at the surprise: Bottom-up attentional control of an active camera system
—Inspired by the expectation-based perception of humans, a surprise-driven active vision system is proposed. This vision system not only considers spatial saliency of objects in ...
Tingting Xu, Quirin Mühlbauer, Stefan Sosnows...
ICRA
2008
IEEE
216views Robotics» more  ICRA 2008»
15 years 10 months ago
Active robot calibration algorithm
— This paper presents a new updating algorithm to reduce the complexity of computing an observability index for kinematic calibration of robots. An active calibration algorithm i...
Yu Sun, John M. Hollerbach
PERCOM
2003
ACM
15 years 9 months ago
Recognition of Human Activity through Hierarchical Stochastic Learning
Seeking to extend the functional capability of the elderly, we explore the use of probabilistic methods to learn and recognise human activity in order to provide monitoring suppor...
Sebastian Lühr, Hung Hai Bui, Svetha Venkates...
CORR
2010
Springer
141views Education» more  CORR 2010»
15 years 4 months ago
Agnostic Active Learning Without Constraints
We present and analyze an agnostic active learning algorithm that works without keeping a version space. This is unlike all previous approaches where a restricted set of candidate...
Alina Beygelzimer, Daniel Hsu, John Langford, Tong...
ICMCS
2009
IEEE
115views Multimedia» more  ICMCS 2009»
15 years 1 months ago
A framework to detect and classify activity transitions in low-power applications
Minimizing the number of computations a low-power device makes is important to achieve long battery life. In this paper we present a framework for a low-power device to minimize t...
Jeffrey Boyd, Hari Sundaram