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COGCOM
2010
107views more  COGCOM 2010»
13 years 3 months ago
Where to Look Next? Combining Static and Dynamic Proto-objects in a TVA-based Model of Visual Attention
To decide ``Where to look next ?'' is a central function of the attention system of humans, animals and robots. Control of attention depends on three factors, that is, lo...
Marco Wischnewski, Anna Belardinelli, Werner X. Sc...
ICCV
2009
IEEE
1335views Computer Vision» more  ICCV 2009»
14 years 10 months ago
Top-Down Color Attention for Object Recognition
Generally the bag-of-words based image representation follows a bottom-up paradigm. The subsequent stages of the process: feature detection, feature description, vocabulary cons...
Fahad Shahbaz Khan, Joost van de Weijer, Maria Van...
RAS
2008
156views more  RAS 2008»
13 years 5 months ago
Curious George: An attentive semantic robot
State-of-the-art methods have recently achieved impressive performance for recognising the objects present in large databases of pre-collected images. There has been much less foc...
David Meger, Per-Erik Forssén, Kevin Lai, S...
SAC
2009
ACM
14 years 17 days ago
Attention driven visual processing for an interactive dialog robot
In this paper we propose an attention-based vision system for the JAST interactive dialog robot. The robotic vision system incorporates three submodules: object recognition, gestu...
Thomas Müller, Alois Knoll
ICMCS
2005
IEEE
340views Multimedia» more  ICMCS 2005»
13 years 11 months ago
Adaptive local context suppression of multiple cues for salient visual attention detection
Visual attention is obtained through determination of contrasts of low level features or attention cues like intensity, color etc. We propose a new texture attention cue that is s...
Yiqun Hu, Deepu Rajan, Liang-Tien Chia