A Framework for Model-Based Tracking Experiments in Image Sequences

Abstract

Motris, an integrated system for model-based tracking research, has been designed modularly to study the effects of algorithmic variations on tracking results. Motris attempts to avoid introducing bias into the relative assessment of alternative approaches. Such a bias may be caused by differences of implementation and parameterization if the component approaches are evaluated in separate testing environments. Tracking results are evaluated automatically on a significant test sample in order to quantify the effects of different combinations of alternatives. The Motris system environment thus allows an in-depth comparison between the so-called 'Edge-Element Association' approach documented in Haag and Nagel (1999) and the more recent 'Expectation-Maximization' approach reported by Pece and Worrall (2002).

Initialization of Model-Based Vehicle Tracking in Video Sequences of Inner-City Intersections

“…Our own search for relevant archival publications-see Dahlkamp et al (2007)-confirms this finding and here extends its validity even up to the immediate past. Our subsequent discussion will be restricted to publications treating questions which are directly associated with our subject.…”

“…In addition, the redesign aimed at creating a system which also operates more robustly than Xtrack to the extent possible without introducing changes of a more fundamental nature. The combined effects of these local algorithmic changes have been studied extensively with the conclusion that the Motris-system without automatic initialization yields results at least as good as those obtained earlier using the Xtrack-system, provided the same initialization steps are used in both systems, see Dahlkamp et al (2007).…”

“…A new system, Motris, had been designed, implemented, and shown to achieve at least the tracking rate obtained earlier with Xtrack, as reported in Dahlkamp et al (2007). Usually video-based vehicle tracking assumes that a vehicle will continue its steady-state motion.…”

A cognitive vision approach to early pest detection in greenhouse crops

“…In (ElHelly et al, 2004), the authors describe a biological expert system enhanced with vision techniques, while in our system it is rather the vision system which is enhanced by knowledge-based facilities. Closer to our approach, an experimentation framework, named Motris, is proposed in (Dahlkamp et al, 2007). This framework for 3D-model based tracking is flexible and modular to compare and combine algorithms; in our case this is the role of the program supervision system.…”

Combining shadow detection and simulation for estimation of vehicle size and position

“…As said in (Dahlkamp et al, 2004(Dahlkamp et al, , 2007, switching from 2D tracking in the image plane to 3D tracking in the scene domain often results in a substantially reduced failure rate, because more prior knowledge about the objects can be utilized. For example, foreground regions are not always homogeneous, and we need some criteria to merge regions that are likely to belong to the same object.…”