Robust Color Object Detection Using Spatial-Color Joint Probability Functions

Object detection in unconstrained images is an important image understanding problem with many potential applications. There has been little success in creating a single algorithm that can detect arbitrary objects in unconstrained images; instead, algorithms typically must be customized for each specific object. Consequently, it typically requires a large number of exemplars (for rigid objects) or a large amount of human intuition (for non-rigid objects) to develop a robust algorithm. We present a robust algorithm designed to detect a class of compound color objects given a single model image. A compound color object is defined as having a set of multiple, particular colors arranged spatially in a particular way, including flags, logos, cartoon characters, people in uniforms, etc. Our approach is based on a particular type of spatial-color joint probability function called the color edge cooccurrence histogram (CECH). In addition, our algorithm employs perceptual color naming to handl...

• Type: Conference
• Year: 2004
• Where: CVPR
• Authors: David J. Crandall, Jiebo Luo
• Keywords: Color Edge Cooccurrence, Compound Color Object, Computer Vision, CVPR 2004, Related Algorithm, Robust Algorithm, Single Algorithm