Dynamic textures (DT) are videos of non-rigid dynamical objects, such as fire and waves, which constantly change their shape and appearance over time. Most of the prior work on DT analysis dealt with the classification of videos of a single DT or the segmentation of videos containing multiple DTs. In this paper, we consider the problem of joint segmentation and categorization of videos of multiple DTs under varying viewpoint, scale, and illumination conditions. We formulate this problem of assigning a class label to each pixel in the video as the minimization of an energy functional composed of two terms. The first term measures the cost of assigning a DT category to each pixel. For this purpose, we introduce a bag of dynamic appearance features (BoDAF) approach, in which we fit each video with a linear dynamical system (LDS) and use features extracted from the parameters of the LDS for classification. This BoDAF approach can be applied to the whole video, thus providing a framework fo...