  In-line digital holography is a valuable tool for sizing, locating and
tracking micro- or nano-objects in a volume. When a parametric imaging model is
available, Inverse Problems approaches provide a straightforward estimate of
the object parameters by fitting data with the model, thereby allowing accurate
reconstruction. As recently proposed and demonstrated, combining pixel
super-resolution techniques with Inverse Problems approaches improves the
estimation of particle size and 3D-position. Here we demonstrate the accurate
tracking of colloidal particles in Brownian motion. Particle size and
3D-position are jointly optimized from video holograms acquired with a digital
holographic microscopy set up based on a "low-end" microscope objective
($\times 20$, $\rm NA\ 0.5$). Exploiting information redundancy makes it
possible to characterize particles with a standard deviation of 15 nm in size
and a theoretical resolution of 2 x 2 x 5 nm$^3$ for position under additive
white Gaussian noise assumption.
