I obtained a Masters of Engineering (MEng) in Computer Science (2010) and a Masters of Philosophy (MPhil) in Computer Vision & Machine Learning (2014) both from Imperial College, London. In between these, I worked as a software engineer at Goldman Sachs for 2 years.
My previous research interests were focussed on Random Forests, mostly applied to pose estimation, both for articulated hand pose and for multiple instances of textureless 3D objects. This research resulted in two conference publications (CVPR and ECCV) and two journal submissions (under review for PAMI) as well as two filed patents. For more information, see below.
Currently, I am the UK Lead Research Engineer at Blippar. In this role, I co-wrote the augmented reality tracking engine for mobile devices, currently used by our app. However, in the more recent months I have shifted my focus to deep learning being applied to large-scale visual object recognition (Blippar’s visual browser). Our work in this field has been showcased in many major news outlets such as The Daily Mail, The Telegraph and The Wall Street Journal. Additionally, it has been demoed on major TV stations such as Bloomberg CNBC, Fox News NY and BBC London News.
…who knows, get in contact with me at email@example.com
A. Tejani, D. Tang, R. Kouskouridas, T-K. Kim
Latent-Class Hough Forests for 3D Object Detection and Pose Estimation Proc. of European Conference on Computer Vision (ECCV), Zurich, Switzerland, 2014.
[PDF][Demo on YouTube][Project Page]
D. Tang, A. Tejani*, H.J. Chang*, T-K. Kim
Latent Regression Forest: Structured Estimation of 3D Hand Posture Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA, 2014. *indicates equal contribution
[PDF][Demo on YouTube]
A. Tejani*, R. Kouskouridas*, A. Doumanoglou, D. Tang, T-K. Kim
Latent-Class Hough Forests for 6 DoF Object Pose Estimation Under review for IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI). *indicates equal contribution
U.S. [61/831,255]: Estimator Training Method and Pose Estimating Method Using Depth Image
Korea [10-2013-0131658]: Estimator Training Method and Pose Estimating Method Using Depth Image