We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...
Standard optical flow methods for motion or disparity estimation use a brightness constancy constraint equation (BCCE). This BCCE either handles a moving camera imaging a non-movi...
Estimation of optical flow and physically motivated brightness changes can be formulated as parameter estimation in linear models. Accuracy of this estimation heavily depends on t...
Abstract. Motion estimation is essential in a variety of image processing and computer vision tasks, like video coding, tracking, directional filtering and denoising, scene analys...
Abstract. Differential motion estimation is based on detecting brightness changes in local image structures. Filters approximating the local gradient are applied to the image seque...
Abstract. Junctions play an important role in motion analysis. Approaches based on the structure tensor have become the standard for junction detection. However, the structure tens...
Abstract Image sequence processing techniques are an essential tool for the experimental investigation of dynamical processes such as exchange, growth, and transport processes. The...
Under certain assumptions, a moving camera can be self-calibrated solely on the basis of instantaneous optical flow. However, due to a fundamental indeterminacy of scale, instanta...
Anton van den Hengel, Wojciech Chojnacki, Michael ...
We present a variational approach for segmenting the image plane into regions of piecewise parametric motion given two or more frames from an image sequence. Our model is based on ...