Context-Based Vision: Recognizing Objects Using Information from Both 2D and 3D Imagery
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On the Spatial Statistics of Optical Flow
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Context Driven Focus of Attention for Object Detection
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Integrating Visual Context and Object Detection within a Probabilistic Framework
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Real-Time Face Tracking for Context-Aware Computing
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Global Context Extraction for Object Recognition Using a Combination of Range and Visual Features
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Estimation of Object Position Based on Color and Shape Contextual Information
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Context-Based Reasoning Using Ontologies to Adapt Visual Tracking in Surveillance
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Using visual context and region semantics for high-level concept detection
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Computational visual attention systems and their cognitive foundations: A survey
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A realistic benchmark for visual indoor place recognition
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A first glimpse of cryptography's Holy Grail
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Using the forest to see the trees: exploiting context for visual object detection and localization
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Scene Categorization by Introducing Contextual Information to the Visual Words
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Single vs. population cell coding: gaze movement control in target search
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Proceedings of the Workshop on Use of Context in Vision Processing
Multi-modal Semantic Place Classification
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Scene categorization via contextual visual words
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Comparing compact codebooks for visual categorization
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An analysis of automatic gender classification
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Recognizing activities with multiple cues
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A framework for visual-context-aware object detection in still images
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Context based object categorization: A critical survey
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Scene classification based on local autocorrelation of similarities with subspaces
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Semantic fusion of laser and vision in pedestrian detection
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Content without context is meaningless
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Context modeling in computer vision: techniques, implications, and applications
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A unified context assessing model for object categorization
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Context-based automatic local image enhancement
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Learning a context aware dictionary for sparse representation
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Contextually guided semantic labeling and search for three-dimensional point clouds
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Video event description in scene context
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Object class detection: A survey
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Branch&Rank for Efficient Object Detection
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Image annotation by modeling Supporting Region Graph
Applied Intelligence
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There is general consensus that context can be a rich source of information about an object's identity, location and scale. In fact, the structure of many real-world scenes is governed by strong configurational rules akin to those that apply to a single object. Here we introduce a simple framework for modeling the relationship between context and object properties based on the correlation between the statistics of low-level features across the entire scene and the objects that it contains. The resulting scheme serves as an effective procedure for object priming, context driven focus of attention and automatic scale-selection on real-world scenes.