In this paper, we show that a better performance can be achieved by training a keypoint detector to only find those points that are suitable to the needs of the given task. We demo...
Christoph Strecha, Albrecht Lindner, Karim Ali, Pa...
We propose an approach to activity recognition based on detecting and analyzing the sequence of objects that are being manipulated by the user. In domains such as cooking, where m...
The Local Outlier Factor (LOF) is a very powerful anomaly detection method available in machine learning and classification. The algorithm defines the notion of local outlier in...
We present a two-layer hierarchical formulation to exploit different levels of contextual information in images for robust classification. Each layer is modeled as a conditional f...
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...