#HIDDEN MARKOV MODEL MATLAB ACTIVITY RECOGNITION SOURCE CODE CODE#
Here is a Matlab version of the Mathematica Posit code of the paper:ĭisplay text file of classicPOSIT.m code (4 KB). This method is described in "Model-Based Object Pose in 25 Lines of Code" IJCV 15, pp. POSIT is a fast iterative algorithm for finding the pose (rotation and translation) of an object or scene with respect to a camera when points of the object are given in some object coordinate system and these points are visible in the camera image and recognizable, so that corresponding image points and object points can be listed in the same order. In addition to the Baum-Welch method, the much faster segmental k-means method can be selected for training. State durations can be modeled explicitly by Gamma distributions.Ħ. Training can be accomplished by multiple observation sequences, defined in a file.ĥ. Observation probabilities can be modeled by histograms or by Gaussians.Ĥ. Components of an observation vector can use different numbers of symbols.ģ. We used Tapas Kanungo's HMM C code as a starting point.Ģ. This package contains C++ code for applying Hidden Markov Models (HMMs) to files of observation data. Īuthors: Daniel DeMenthon and Marc Vuilleumier The source code and mex files for these three functions can be downloaded as part of the excellent TSTOOL package. In addition, the Matlab code uses nearest neighbor and range search functions nn_prepare, nn_search and range_search. The C code provided for these files will probably need to be recompiled into mex files appropriate for your CPU. Note that the Matlab code calls several mex files.
Multimedia Tools and Applications (MTAP), pp. This package contains the Matlab code developed to implement the video retrieval method described in the paper by Daniel DeMenthon and David Doermann, "Video Retrieval of Near-Duplicates using k-Nearest Neighbor Retrieval of Spatio-Temporal Descriptors". Hierarchical Mean Shift, Space-Time Segmentation and Action Recognition (Matlab) All Code is Free for Download, Reuse, and Modification