Classifying an event captured in an image is useful for understanding the contents of the image. The captured event provides context to refine models for the presence and appearan...
We present a new method for classification with structured
latent variables. Our model is formulated using the
max-margin formalism in the discriminative learning literature.
We...
We describe an unsupervised method to segment objects detected in images using a novel variant of an interest point template, which is very efficient to train and evaluate. Once a...
Himanshu Arora, Nicolas Loeff, David A. Forsyth, N...
The ability to detect object size, location and movement is essential for a visual system in either a biological or man made environment. In this paper we present a model for esti...
We present a discriminative part-based approach for the recognition of object classes from unsegmented cluttered scenes. Objects are modeled as flexible constellations of parts co...