Rapid improvement in computing power, cheap sensing, and more flexible algorithms are
facilitating increased development of real-time video surveillance and monitoring systems …

Despite the impressive predictive performance exhibited by deep learning across various
domains, its application in research models within the social and behavioral sciences has …

From the Publisher: Empirical Evaluation Techniques in Computer Vision presents methods
that allow comparative assessment of algorithms and the accompanying benefits: places …

It is frequently remarked that designers of computer vision algorithms and systems cannot
reliably predict how algorithms will respond to new problems. A variety of reasons have …

We describe a generic methodology for evaluating the labeling performance of feature
detectors. We describe a method for generating a test set and apply the methodology to the …

Algebraic projective geometry, with its multilinear relations and its embedding into
Grassmann-Cayley algebra, has become the basic representation of multiple view …

Previous performance evaluation of range image segmentation algorithms has depended
on manual tuning of algorithm parameters, and has lacked a basis for a test of the …

The output distribution of a neural network (NN) over the entire input space captures the
complete input-output mapping relationship, offering in-sights toward a more comprehensive …

We consider the relationship between the performance characteristics of vision algorithms
and algorithm design. In the first part we discuss the issues involved in testing. A description …

As computer vision systems are increasingly developed and tested in the real-world, there is
a significant need to formalize the process of system design and analysis so that engineers …