Process and Implementation: Optical Flow

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Process and Implementation Optical Flow First, I needed to investigate methods to compute optical flow. From the description in the paper, it seemed as if they were using the Lucas-Kanade method. This method assumes that optical flow is constant in a small window. It is a highly used method of computing optical flow and is found in several libraries. The library I utilized was created by Piotr Dollar, from the University of California, San Diego (1). This toolbox also implements a cross-correlation method of computing optical flow, as well as the Horn & Schunck method. I tested all three of these methods and determined that the Lucas-Kanade method was the best choice for this application. In class, there was a suggestion to investigate a hierarchical version of the Lucas-Kanade method to more accurately calculate optical flow, since it is an integral part of this paper. I tested a toolbox (2) that was written by Sohaib Khan, who was a student of Mubarak Shah at the University of Central Florida. This code produced results that were much more highly susceptible to noise, and I determined that the better choice was the original toolbox. These results can be seen in Figure 1. Figure 1: Lucas-Kanade Optical Flow Method (left) vs. Hierarchical Lucas-Kanade Optical Flow Method (right) Generalized Social Force for Particle Advection and Calculation of the Interaction Force The paper presents a method of using particle advection to estimate the flow of objects through a scene. Since crowd scenes are cluttered and difficult to track microscopically, the authors proposed this macroscopic method of overlaying a grid of particles on the scene and advecting them via optical flow to model the movement of the crowd. This... ... middle of paper ... ... is unclear and a mystery to me. I also would be interested in implementing the concept in a way other than through particle advection, as I feel that it loses a lot of data by not evenly covering the scene in each clip. Works Cited 1. Dollar, Piotr. Piotr's Matlab Image and Video Toolbox. Piotr Dollar. [Online] February 22, 2010. [Cited: March 17, 2010.] 2. Khan, Sohaib. Source Code. Mubarak Shah. [Online] [Cited: March 17, 2010.] 3. Blei, David. Latent Dirichlet Allocation in C. David Blei. [Online] [Cited: March 17, 2010.] 4. Mochihashi, Daichi. lda, a Latent Dirichlet Allocation package. Daichi Mochihashi. [Online] December 4, 2004. [Cited: March 17, 2010.]

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