Robust Particle Filtering for Object Tracking

Abstract. This paper addresses the filtering problem when no assumption about linearity or gaussianity is made on the involved density functions. This approach, widely known as particle filtering, has been explored by several previous algorithms, including Condensation. Although it represents a new paradigm and some results have been achieved, it has several unpleasant behaviours. We highlight these misbehaviours and propose an algorithm which deals with them. A test-bed, which allows proof-testing of new approaches, has been developed. The proposal has been successfully tested using both synthetic and real sequences.

• Type: Conference
• Year: 2005
• Where: ICIAP
• Authors: Daniel Rowe, Ignasi Rius, Jordi Gonzàlez, Juan José Villanueva
• Keywords: Density Functions, ICIAP 2005, Image Processing, Linearity, Unpleasant Behaviours