Discriminative learning is challenging when examples are sets of features, and the sets vary
in cardinality and lack any sort of meaningful ordering. Kernel-based classification methods …

" A picture is worth one thousand words". This proverb comes from Confucius-a Chinese
philosopher about 2500 years ago. Now, the essence of these words is universally …

Part structure and articulation are of fundamental importance in computer and human vision.
We propose using the inner-distance to build shape descriptors that are robust to articulation …

Nearest-Neighbor Methods in Learning and Vision | Guide books skip to main content ACM
Digital Library home ACM Association for Computing Machinery corporate logo Google, Inc …

This book introduces the fundamental concepts of modern digital image processing. It aims
to help the students, scientists, and practitioners to understand the concepts through clear …

In numerous domains it is useful to represent a single example by the set of the local
features or parts that comprise it. However, this representation poses a challenge to many …

The standard L2-norm support vector machine (SVM) is a widely used tool for classification
problems. The L1-norm SVM is a variant of the standard L2-norm SVM, that constrains the …

It is often frustrating for drivers to find parking spaces, and parking itself is costly in almost
every major city in the world. Here we propose a crowdsourcing solution by exploiting …

We implement pedestrian dead reckoning (PDR) for indoor localization. With a waist-
mounted PDR based system on a smart-phone, we estimate the user's step length that …

We present an approach for reacquisition of detected moving objects. We address the
tracking problem by modeling the appearance of the moving region using stochastic models …