Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Optical flow estimation is a fundamental and ill-posed problem in computer vision. To recover a dense flow field, appropriate spatial constraints have to be enforced. Recent ad...
In recent years, depth cameras have become a widely available sensor type that captures depth images at realtime frame rates. Even though recent approaches have shown that 3D pose...
Andreas Baak, Meinard Muller, Gaurav Bharaj, Hans-...
In this paper, we propose a physically-based dynamical model for tracking. Our model relies on Newton’s second law of motion, which governs any real-world dynamical system. As a...
In this paper we propose a new method for the simultaneous segmentation and 3D reconstruction of interest point based articulated motion. We decompose a set of point tracks into r...
We introduce a spatially dense variational approach to estimate the calibration of multiple cameras in the context of 3D reconstruction. We propose a relaxation scheme which allow...
We present a method whereby an embodied agent using visual perception can efficiently create a model of a local indoor environment from its experience of moving within it. Our me...
Grace Tsai, Changhai Xu, Jingen Liu, Benjamin Kuip...
As a recently proposed technique, sparse representation based classification (SRC) has been widely used for face recognition (FR). SRC first codes a testing sample as a sparse lin...
Facial micro-expressions are rapid involuntary facial expressions which reveal suppressed affect. To the best knowledge of the authors, there is no previous work that successfully...
Tomas Pfister, Xiaobai Li, Guoying Zhao, Matti Pie...
Progress in action recognition has been in large part due to advances in the features that drive learning-based methods. However, the relative sparsity of training data and the ri...