Device and method for detecting object and device and method for group learning

An object detecting method for detecting if a given grayscale image is an object, the method comprising:

• a weak discriminating step of computing an estimate indicating that the grayscale image is an object or not according to a characteristic quantity that is equal to the difference of the luminance values of two pixels at two different positions that is learned in advance for each of a plurality of weak discriminators;
• and
• a discriminating step of judging if the grayscale image is an object according to the estimate computed by one of or the estimates computed by more than one of the plurality of weak discriminators.

An ensemble learning device for ensemble learning using learning samples of a plurality of grayscale images provided with respective correct answers telling if each of the grayscale images is an object, the device comprising:

• a learning means for learning a plurality of weak discriminators for outputting an estimate indicating that the grayscale image is an object or not in a group, using a characteristic quantity that is equal to the difference of the luminance values of two pixels at arbitrarily selected two different positions as input;
• and
• a combining means for selectively combining more than one weak discriminator from the plurality of weak discriminators according to a predetermined learning algorithm.

An ensemble learning method of using learning samples of a plurality of grayscale images provided with respective correct answers telling if each of the grayscale images is an object, the device comprising:

• a learning step of learning a plurality of weak discriminators for outputting an estimate indicating that the grayscale image is an object or not in a group, using a characteristic quantity that is equal to the difference of the luminance values of two pixels at arbitrarily selected two different positions as input;
• and
• a combining step of selectively combining more than one weak discriminator from the plurality of weak discriminators according to a predetermined learning algorithm.

An object detecting device for detecting if a given grayscale image is an object, the device comprising:

• a plurality of weak discriminating units configured to compute an estimate indicating that the grayscale image is an object or not according to a characteristic quantity that is equal to the difference of the luminance values of two pixels at two different positions;
• and
• a discriminating unit configured to judge if the grayscale image is an object according to the estimate computed by one of or the estimates computed by more than one of the plurality of weak discriminating units.

A detecting device for detecting objects in an image comprised of pixels comprising:

• a discriminating unit for determining differences between pixel values of two pixels at two different positions and outputting an estimate of probability that the image includes an object, based on said differences;
• and
• a judging unit using learnt estimates for judging whether the image includes an object according to the estimate.

A detecting method for detecting objects in an image comprised of pixels comprising the steps of:

• determining differences between pixel values of two pixels at two different positions and outputting an estimate of probability that the image includes an object, based on said differences;
• and
• using learnt estimates for judging whether the image includes an object according to the estimate.