Object Recognition Using Composed Receptive Field Histograms of Higher Dimensionality

Recent work has shown that effective methods for recognising objects or spatio-temporal events can be constructed based on receptive field responses summarised into histograms or other histogram-like image descriptors. This paper presents a set of composed histogram features of higher dimensionality, which give significantly better recognition performance compared to the histogram descriptors of lower dimensionality that were used in the original papers by Swain & Ballard (1991) or Schiele & Crowley (2000). The use of histograms of higher dimensionality is made possible by a sparse representation for efficient computation and handling of higher-dimensional histograms. Results of extensive experiments are reported, showing how the performance of histogram-based recognition schemes depend upon different combinations of cues, in terms of Gaussian derivatives or differential invariants applied to either intensity information, chromatic information or both. It is shown that there e...

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: Oskar Linde, Tony Lindeberg
• Keywords: Better Recognition Performance, Computer Vision, Histogram Features, Histogram-like Image Descriptors, ICPR 2004