The error associated with estimating the local concentration of particles observed in digital videos of the inner wall of a circulating fluidized bed (CFB) riser is evaluated. Understanding the dynamics of these rapidly moving particles will allow researchers to design cleaner and more efficient CFB facilities. However, the seemingly random motion exhibited by the particles in three dimensions, coupled with the varying image quality, make it difficult to extract the required information from the images. A method has been developed for automatically detecting particles from a video sequence. By exploiting the presence of specular reflections, individual particles are identified along the focal plane by an image filter specifically designed for this purpose. An evaluation of the proposed method indicates its potential to estimate particle count, location, and concentration in an efficient and reliable manner. Published by Elsevier B.V.