Boris Schauerte
Papers
11
Total Citations
194
H-Index
8
About
Boris Schauerte's research lies at the intersection of computer vision, robotics, and human-robot interaction, with a central focus on multimodal saliency and attention. His work has pioneered how robots can naturally focus on relevant stimuli—whether visual or acoustic—to achieve joint attention with human partners. His most influential contribution is a saliency-based model that integrates verbal and non-verbal cues (such as pointing gestures and spoken references) to identify and segment referent objects, enabling more intuitive interaction. This work, published in 2010, has garnered 46 citations and remains foundational in the field. Schauerte also introduced Bayesian surprise for detecting salient acoustic events (28 citations), and developed methods for learning to guide visual saliency in real-time human-robot dialogue (23 citations). His research extends to multi-camera smart environments and web-based learning of color models for robust object recognition. With over 190 total citations across his top papers, Schauerte’s contributions have advanced the design of socially aware robots that can perceive and respond to human communication in complex, dynamic settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2Multimodal saliency-based attention for object-based scene analysis34 citations · 2011
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- 5Multi-modal and multi-camera attention in smart environments17 citations · 2009
- 6Web-Based Learning of Naturalized Color Models for Human-Machine Interaction15 citations · 2010
- 7Multimodal saliency-based attention: A lazy robot's approach10 citations · 2012
- 8Way to Go! Detecting Open Areas Ahead of a Walking Person10 citations · 2015
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