Tag: Sohaib Khan
Eurographics 2015 – Efficient RANSAC for n-gonal Primitive Fitting
Ahsan Abdullah, Reema Bajwa, Syed Rizwan Gilani, Zuha Agha, Saeed Boor Boor, Murtaza Taj, Sohaib Ahmed Khan The 36th Annual Conference of the European Association for Computer Graphics, 2015 Kongresshaus in Zürich, Switzerland, 4th – 8th May, 2015 Abstract We present a modeling approach to automatically fit 3D primitives to point clouds in order to […]
Shape from Angle Regularity – Project Page
Urban architecture is characterized by a profusion of straight lines that meet orthogonally. This simple observation leads to a flexible definition of the man-made world and the distortion in these regular angles serves as a new shape-from-X cue. This project formulates the idea and explores its applications in various scenarios in detail. Publications Some initial results […]
Press Release on Carnegie Mellon News
Our joint research project with Iain Matthews at Disney Research Pittsburgh and Yaser Sheikh and Tomas Simon at Carnegie Mellon University is covered by Carnegie Mellon News. To quote from the press release: Computer graphic artists who produce computer-animated movies and games spend much time creating subtle movements such as expressions on faces, gesticulations on […]
Bilinear Spatiotemporal Basis Models – Project Page
Ijaz Akhter, Tomas Simon, Sohaib Khan, Iain Matthews, Yaser Sheikh Abstract A variety of dynamic objects, such as faces, bodies, and cloth, are represented in computer graphics as a collection of moving spatial landmarks. Spatiotemporal data is inherent in a number of graphics applications including animation, simulation, and object and camera tracking. The principal modes […]
ECCV 2012 – Shape from Angle Regularity
This paper presents a new Shape-from-X method which is applicable for typical man-made environments which have a profusion of orthogonal lines. A full single-view reconstruction method for multi-planar man-made scenes is demonstrated. Authors: Aamer Zaheer, Maheen Rashid, Sohaib Khan, ECCV 2012.
Trajectory Basis for Nonrigid Structure from Motion – Project Page
Ijaz Akhter, Yaser Sheikh, Sohaib Khan, Takeo Kanade Abstract Existing approaches to nonrigid structure from motion assume that the instantaneous 3D shape of a deforming object is a linear combination of basis shapes. These basis are object dependent and therefore have to be estimated anew for each video sequence. In contrast, we propose a dual approach to describe the evolving […]
Correlation Coefficient Based Fast Template Matching Through Partial Elimination – Project Page
Project page of our IEEE Transactions on Image Processing April 2012 paper on “Correlation Coefficient Based Fast Template Matching Through Partial Elimination”. Contains datasets and code.
ToG 2012 – Bilinear Spatiotemporal Basis Models
Our paper in ACM Transactions on Graphics April 2012 presents a fundamentally new way to model time-varying point clouds, that dramatically reduces processing times for common graphics pipeline tasks such as labeling, gap-filling, denoising, and motion touch-up. This is joint work with Carnegie Mellon University and Disney Research Pittsburgh, and has been presented at Siggraph 2012.
TIP 2012 – Correlation Coefficient Based Fast Template Matching Through Partial Elimination
Arif Mahmood, Sohaib Khan IEEE Transactions on Image Processing, Vol 21, No 4, April 2012 Abstract Partial computation elimination techniques are often used for fast template matching. At a particular search location, computations are prematurely terminated as soon as it is found that this location cannot compete already known best-match location. Due to non-monotonic growth […]
ICCV 2011 – Multiview Structure from Motion in Trajectory Space
Aamer Zaheer, Ijaz Akhter, Mohammad Haris Baig, Shabbir Marzban, Sohaib Khan International Conference on Computer Vision, ICCV, 2011 Abstract Most nonrigid objects exhibit temporal regularities in their deformations. Recently it was proposed that these regularities can be parameterized by assuming that the non- rigid structure lies in a small dimensional trajectory space. In this paper, […]
