Novel image feature alphabets for object recognition

Most successful object recognition systems are based on a visual alphabet of quantised gradient orientations. Here, we introduce two richer image feature alphabets for use in object recognition. The two alphabets are evaluated using the PASCAL VOC challenge 2007 dataset. The results show that both alphabets perform as well as or better than the ’standard‘ gradient orientation based one.

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Martin Lillholm, Lewis D. Griffin
• Keywords: Alphabets, Computer Vision, Gradient Orientation, ICPR 2008, Object Recognition