We present an unsupervised, shape-based method for joint clustering of multiple image segmentations. Given two or more closely-related images, such as nearby frames in a video sequ...
Daniel Glasner, Shiv N. Vitaladevuni and Ronen Bas...
We present an unsupervised, shape-based method for joint clustering of multiple image segmentations. Given two or more closely-related images, such as nearby frames in a video seq...
This paper describes a method for establishing dense correspondence between two images in a video sequence (motion) or in a stereo pair (disparity) in case of large displacements....
Moustapha Kardouchi, Janusz Konrad, Carlos V&aacut...
Abstract. This paper describes a novel approach to automatically recover accurate correspondence over various shapes. In order to detect the features points with the capability in ...
We present here a new descriptor for depth images adapted to 2D/3D model matching and retrieving. We propose a representation of a 3D model by 20 depth images rendered from the ve...