General object tracking with a component-based target descriptor

In this paper, we present a component-based visual object tracker for mobile platforms. The core of the technique is a component-based descriptor that captures the structure and appearance of a target in a flexible way. This descriptor can be learned quickly from a single training image and is easily adaptable to different objects. The descriptor is integrated into the observation model of a visual tracker based on the well known Condensation algorithm. We show that the approach is applicable to a large variety of objects and in different environments with cluttered backgrounds and a moving camera. The method is robust to illumination and viewpoint changes and applicable to indoor as well as outdoor scenes.

Authors

• Simone Frintrop

Keywords

• Target tracking
• Cameras
• Robustness
• Mobile robots
• Robot vision systems
• Lighting
• Humans
• Histograms
• Particle tracking
• Robotics and automation
• Object Tracking
• General Object Tracking
• Mobile Platform
• Flexible Way
• Illumination Changes
• Viewpoint Changes
• Feature Maps
• Target Region
• Scale Changes
• Color Space
• Color Map
• Position Of Region
• Particle Filter
• Mobile Robot
• Human Vision
• Color Model
• Map Scale
• Motion Blur
• Integral Image
• Object Appearance
• Color Histogram
• Target Template
• Particle Weight
• Target Part
• Tanimoto Coefficient
• HSV Color
• Motion Model
• Top Right
• Similarity Measure
• Personality Changes