Bio-inspired metaheuristic based visual tracking and ego-motion estimation
2014 (English)Conference paper (Refereed)
The problem of robust extraction of ego-motion from a sequence of images for an eye-in-hand camera configuration is addressed. A novel approach toward solving planar template based tracking is proposed which performs a non-linear image alignment and a planar similarity optimization to recover camera transformations from planar regions of a scene. The planar region tracking problem as a motion optimization problem is solved by maximizing the similarity among the planar regions of a scene. The optimization process employs an evolutionary metaheuristic approach in order to address the problem within a large non-linear search space. The proposed method is validated on image sequences with real as well as synthetic image datasets and found to be successful in recovering the ego-motion. A comparative analysis of the proposed method with various other state-of-art methods reveals that the algorithm succeeds in tracking the planar regions robustly and is comparable to the state-of-the art methods. Such an application of evolutionary metaheuristic in solving complex visual navigation problems can provide different perspective and could help in improving already available methods.
Place, publisher, year, edition, pages
Angers, France: SciTePress , 2014.
Camera tracking, Particle swarm optimization, Planar template based tracking, Visual odometry
IdentifiersURN: urn:nbn:se:bth-6530Local ID: oai:bth.se:forskinfo2EC2A7D1A752EBD0C1257D960037AF7DISBN: 978-989758018-5OAI: oai:DiVA.org:bth-6530DiVA: diva2:834048
International Conference on Pattern Recognition Applications and Methods (ICPRAM)