title: A strategy for the correction of effects of jitter in AMCW lidar images

authors: Streeter, Lee

subjects: Science & Technology

abstract: Full-field range imaging cameras, which are an example of amplitude modulated continuous wave (AMCW) lidar, are subject to multiple error sources. In this paper we consider the possibility that a global jitter and/or drift occurs between the modulation signals to the active illumination source and the camera sensor. A model for jitter is presented and is used to characterise the jitter in a real camera system. Correction of the effects of jitter in real acquired range images is demonstrated by a reduction of the standard deviation of random noise by up to a factor of five, with the best reductions occurring in pixels that receive a strong signal.

text: A strategy for the correction of effects of jitter in AMCW lidar images Full-field range imaging cameras, which are an example of amplitude modulated continuous wave (AMCW) lidar, are subject to multiple error sources. In this paper we consider the possibility that a global jitter and/or drift occurs between the modulation signals to the active illumination source and the camera sensor. A model for jitter is presented and is used to characterise the jitter in a real camera system. Correction of the effects of jitter in real acquired range images is demonstrated by a reduction of the standard deviation of random noise by up to a factor of five, with the best reductions occurring in pixels that receive a strong signal.

year: 2013

title: Racing committees for large datasets

authors: Frank, Eibe

subjects: Machine learning

abstract: This paper proposes a method for generating classifiers from large datasets by building a committee of simple base classifiers using a standard boosting algorithm.  It allows the processing of large datasets even if the underlying base learning algorithm cannot efficiently do so.  The basic idea is to split incoming data into chunks and build a committee based on classifiers build from these individual chunks [3].  Our method extends earlier work in two ways:  (a) the best chunk size is chosen automatically by racing committees corresponding to different chunk sizes, and (b) the committees are pruned adaptively to keep the size of each individual committee as small as possible without negatively affecting accuracy.  This paper shows that choosing an appropriate chunk size automatically is important because the accuracy of the resulting committee can vary significantly with the chunk size.  It also shows that pruning is crucial to make the method practical for large datasets in terms of running time and memory requirements.  Surprisingly, the results demonstrate that pruning can also improve accuracy.

text: Racing committees for large datasets This paper proposes a method for generating classifiers from large datasets by building a committee of simple base classifiers using a standard boosting algorithm.  It allows the processing of large datasets even if the underlying base learning algorithm cannot efficiently do so.  The basic idea is to split incoming data into chunks and build a committee based on classifiers build from these individual chunks [3].  Our method extends earlier work in two ways:  (a) the best chunk size is chosen automatically by racing committees corresponding to different chunk sizes, and (b) the committees are pruned adaptively to keep the size of each individual committee as small as possible without negatively affecting accuracy.  This paper shows that choosing an appropriate chunk size automatically is important because the accuracy of the resulting committee can vary significantly with the chunk size.  It also shows that pruning is crucial to make the method practical for large datasets in terms of running time and memory requirements.  Surprisingly, the results demonstrate that pruning can also improve accuracy.

year: 2002-06-01

title: 'Waitangi and indigenous rights: Revolution, law and legitimacy' by F.M. Brookfield

authors: Melbourne, Hirini

subjects: indigenous rights

abstract: 'Waitangi and Indigenous Rights: Revolution, Law and Legitimacy' book review by Hirini Melbourne.

text: 'Waitangi and indigenous rights: Revolution, law and legitimacy' by F.M. Brookfield 'Waitangi and Indigenous Rights: Revolution, Law and Legitimacy' book review by Hirini Melbourne.

year: 2000-10