1. Use of context in vision processing
- Author
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Anton Nijholt, Yuri Ivanov, Ralph Braspenning, Maja Pantic, Louis-Philippe Morency, Hamid Aghajan, and Ming-Hsuan Yang
- Subjects
Computer science ,intelligent headlight control ,IR-70415 ,HMI-MI: MULTIMODAL INTERACTIONS ,Machine Learning ,METIS-266455 ,Human–computer interaction ,Robustness (computer science) ,Contextual information ,human- human interaction ,Computer vision ,Modalities ,Ambient intelligence ,business.industry ,EWI-17696 ,driving context ,Cognitive neuroscience of visual object recognition ,context-driven event interpretation ,Object recognition ,camera sensors ,statistical relational models ,image/video content analysis ,Vision science ,smart homes ,Enabling ,visual gesture recognition ,Systems design ,Algorithm design ,Artificial intelligence ,business - Abstract
Recent efforts in defining ambient intelligence applications based on user-centric concepts, the advent of technology in different sensing modalities as well as the expanding interest in multi-modal information fusion and situation-aware and dynamic vision processing algorithms have created a common motivation across different research disciplines to utilize context as a key enabler of application-oriented vision systems design. Improved robustness, efficient use of sensing and computing resources, dynamic task assignment to different operating modules as well as adaptation to event and user behavior models are among the benefits a vision processing system can gain through the utilization of contextual information. The Workshop on Use of Context in Vision Processing (UCVP) aims to address the opportunities in incorporating contextual information in algorithm design for single or multi-camera vision systems, as well as systems in which vision is complemented with other sensing modalities, such as audio, motion, proximity, occupancy, and others.
- Published
- 2009
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