One of the Videotrace patent applications has just been accepted by IP Australia.
It’s Patent Number 2007202157
ABSTRACT A method for generating a three dimensional (3D) model of an object is depicted in a two dimensional (2D) image is disclosed, The 2D image includes associated 3D information. The method includes an operator determining a geometric more »
Congratulations to Xi Li, Guosheng Lin, Chunhua Shen, and Anthony Dick on having had ‘Learning Hash Functions Using Column Generation’ accepted as an oral presentation to this year’s ICML. It’s a great result.
An ACVT paper has just been announced as the Spotlight Paper for the September 2012 issue of the IEEE Transactions on Pattern Analysis and Machine Intelligence.
The paper is
Efficient Computation of Robust Weighted Low-Rank Matrix Approximations Using the L₁ Norm
By Anders Eriksson and Anton van den more »
The IEEE Conference on Computer Vision and Pattern Recognition is one of the top 2 in the field and had an acceptance rate this year of 24%. 4 papers accepted is a great result for the group.
The papers are
Sharing Features in Multi-class Boosting via Group Sparsity, Sakrapee Paisitkriangkrai, Chunhua Shen, Anton more »
ACVT researchers have 2 articles in the latest IEEE Transactions on Pattern Analysis and Machine Intelligence from April 2012 (vol. 34 no. 4). PAMI is the best journal in the field.
The papers are
Accelerated Hypothesis Generation for Multistructure Data via Preference Analysis, Tat-Jun Chin, Jin Yu, David Suter, more »
ACVT researchers have had 5 papers accepted to The International Conference on Computer Vision 2011, which will be held in Barcelona in November.
The paper Real-time Modelling for AR Applications won second prize in the best paper awards at the International Symposium on Mixed and Augmented Reality 2010 in Seoul, Korea.
The paper describes a method for generating 3D models of objects which requires minimal user interaction. The motivation was the desire to allow users to create special more »
Our paper
Efficient Computation of Robust Low-Rank Matrix Approximations in the Presence of Missing Data using the L1 Norm, Anders Eriksson and Anton van den Hengel, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2010), June 2010, San Francisco, USA, IEEE 2009
Anton van den Hengel recently attended ISMAR 2009 in Orlando, Florida, presenting the paper ‘In Situ Image-based Modeling’ by Anton, Rhys Hill, Ben Ward, and Anthony Dick

