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WAPCV
2007
Springer
15 years 3 months ago
Learning to Attend - From Bottom-Up to Top-Down
The control of overt visual attention relies on an interplay of bottom-up and top-down mechanisms. Purely bottom-up models may provide a reasonable account of the looking behaviors...
Hector Jasso, Jochen Triesch
CVPR
2011
IEEE
14 years 6 months ago
Saliency Estimation Using a Non-Parametric Low-Level Vision Model
Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to constru...
Naila Murray, Maria Vanrell, Xavier Otazu, C. Alej...
ARVLSI
1999
IEEE
162views VLSI» more  ARVLSI 1999»
15 years 1 months ago
Conjunction Search Using a 1-D, Analog VLSI-based, Attentional Search/Tracking Chip
The ability of animals to select a limited region of sensory space for scrutiny is an important factor in dealing with cluttered or complex sensory environments. Such an attention...
Timothy K. Horiuchi, Ernst Niebur
106
Voted
ACII
2011
Springer
13 years 9 months ago
A Psychologically-Inspired Match-Score Fusion Model for Video-Based Facial Expression Recognition
Communication between humans is rich in complexity and is not limited to verbal signals; emotions are conveyed with gesture, pose and facial expression. Facial Emotion Recognition ...
Albert Cruz, Bir Bhanu, Songfan Yang
ICMI
2005
Springer
104views Biometrics» more  ICMI 2005»
15 years 2 months ago
Analyzing and predicting focus of attention in remote collaborative tasks
To overcome the limitations of current technologies for remote collaboration, we propose a system that changes a video feed based on task properties, people’s actions, and messa...
Jiazhi Ou, Lui Min Oh, Susan R. Fussell, Tal Blum,...