Patent ID: 7286707

Claim:
An object-detection method, based on a multi-class cascade framework, and provided for a computer-vision system to detect objects in an image data, and comprising the following steps: (I) scanning multiple rectangles of said image data; (II) utilizing integral images to calculate projections inside said image data; and (III) performing multi-class classification of said rectangles according to the results of projection calculation, wherein said image-detection system utilizes a Multi-class Bhattacharyya Boost (MBH-Boost) algorithm to perform a multi-class detection, said MBH-Boost algorithm including the following steps: (A) providing training data D Γ of a set┌ of multiple classes, a set Φ of projection directions of weak learners, and a number of iteration T; (B) in the “t”th iteration, working out an optimal projection direction φ t according to a weighted value W t x (i) of each component of said training data D Γ ; (C) updating said weighted value W t x (i) into w t+1 x (i) according to the classification results of said φ t ; and (D) after T iterations of (B) and (C), working out a vector-valued classifier F, which can be used as decision boundaries, wherein said classifier F includes calculation results H A , H B , H C . . . respectively corresponding to each class in said set Γ and positive values of said calculation results H A , H B , H C . . . respectively corresponding to each class in said set Γ is used as classification standards.