Machine Learning
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Contextual Priming for Object Detection
International Journal of Computer Vision
Context-based vision system for place and object recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Patchlets: a method of interpreting correlation stereo three-dimensional data
Patchlets: a method of interpreting correlation stereo three-dimensional data
Machine Learning
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pose estimation and map building with a Time-Of-Flight-camera for robot navigation
International Journal of Intelligent Systems Technologies and Applications
Efficient Gaussian process classification using random decision forests
Pattern Recognition and Image Analysis
Large-scale Gaussian process classification using random decision forests
Pattern Recognition and Image Analysis
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It has been highlighted by many researchers, that the use of context information as an additional cue for high-level object recognition is important to close the gap between human and computer vision. We present an approach to context extraction in the form of global features for place recognition. Based on an uncalibrated combination of range data of a time-of-flight (ToF) camera and images obtained from a visual sensor, our system is able to classify the environment in predefined places (e.g. kitchen, corridor, office) by representing the sensor data with various global features. Besides state-of-the-art feature types, such as power spectrum models and Gabor filters, we introduce histograms of surface normals as a new representation of range images. An evaluation with different classifiers shows the potential of range data from a ToF camera as an additional cue for this task.