This paper introduces a geometrically inspired large-margin classifier that can be a better alternative to the Support Vector Machines (SVMs) for the classification problems with ...
Categorizing web-based videos is an important yet challenging task. The difficulties arise from large data diversity within a category, lack of labeled data, and degradation of vi...
In this paper we derive formal constraints relating terrain elevation and observed cast shadows. We show how an optimisation framework can be used to refine surface estimates usin...
In this paper, we present an appearance-based method for person re-identification. It consists in the extraction of features that model three complementary aspects of the human ap...
In this paper, we present a 3D X-Ray Transform based multilinear feature extraction and classification method for Digital Multi-focal Images (DMI). In such images, morphological i...
This paper presents a novel mixture-of-experts framework for pedestrian classification with partial occlusion handling. The framework involves a set of component-based expert clas...
Markus Enzweiler, Angela Eigenstetter, Bernt Schie...
This paper addresses the problem of recognizing freeform 3D objects in point clouds. Compared to traditional approaches based on point descriptors, which depend on local informati...
Bertram Drost, Markus Ulrich, Nassir Navab, Slobod...
Sparse coding which encodes the original signal in a sparse signal space, has shown its state-of-the-art performance in the visual codebook generation and feature quantization pro...
This paper presents a codebook learning approach for image classification and retrieval. It corresponds to learning a weighted similarity metric to satisfy that the weighted simil...
We present an efficient and scalable technique for spatiotemporal segmentation of long video sequences using a hierarchical graph-based algorithm. We begin by oversegmenting a vol...
Matthias Grundmann, Vivek Kwatra, Mei Han, Irfan E...