System for detecting salient objects in images

A system for detecting salient objects in images, the system comprising:

• one or more processors and a memory, the memory being a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions, the one or more processors perform operations of:
• mapping an input image into a frequency domain having a spectral magnitude;
• replacing the spectral magnitude with weights from a weight matrix W;
• transforming the frequency domain with the weights to a saliency map in the image domain, the saliency map having pixels with pixel values:
• performing a squaring operation on the saliency map by squaring the pixel values to generate a pixel-value altered saliency map such that all values in the pixel-value altered saliency map are nonnegative;
• generating a final saliency map by filtering the pixel-value altered saliency map;
• generating the weight matrix W, such that the weight matrix W is a foreground weight matrix F divided by the background weight matrix B, wherein the foreground weight matrix F is an average spectral magnitude of foreground regions from a training set, and wherein the background weight matrix B is an average spectral magnitude of background images;
• designating a region within the final saliency map as an object;
• classifying an object within the final saliency map;
• displaying the classification on a display device;
• causing an autonomous vehicle to perform a maneuver to avoid collision with the object;
• and
• wherein in filtering the pixel-value altered saliency map, salient edges within the pixel-value altered saliency map are blurred into salient regions.

A computer program product for detecting salient objects in images, the computer program product comprising:

• a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions by one or more processors, the one or more processors perform operations of:
• mapping an input image into a frequency domain having a spectral magnitude;
• replacing the spectral magnitude with weights from a weight matrix W;
• transforming the frequency domain with the weights to a saliency map in the image domain, the saliency map having pixels with pixel values;
• performing a squaring operation on the saliency map by squaring the pixel values to generate a pixel-value altered saliency map such that all values in the pixel-value altered saliency map are nonnegative;
• generating a final saliency map by filtering the pixel-value altered saliency map;
• and
• generating the weight matrix W, such that the weight matrix W is a foreground weight matrix F divided by the background weight matrix B, wherein the foreground weight matrix F is an average spectral magnitude of foreground regions from a training set, and wherein the background weight matrix B is an average spectral magnitude of background images.

A computer program product for detecting salient objects in images, the computer program product comprising:

• a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions by one or more processors, the one or more processors perform operations of:
• mapping an input image into a frequency domain having a spectral magnitude;
• replacing the spectral magnitude with weights from a weight matrix W;
• transforming the frequency domain with the weights to a saliency map in the image domain, the saliency map having pixels with pixel values;
• performing a squaring operation on the saliency map by squaring the pixel values to generate a pixel-value altered saliency map such that all values in the pixel-value altered saliency map are nonnegative;
• generating a final saliency map by filtering the pixel-value altered saliency map;
• generating the weight matrix W, such that the weight matrix W is a foreground weight matrix F divided by the background weight matrix B, wherein the foreground weight matrix F is an average spectral magnitude of foreground regions from a training set, and wherein the background weight matrix B is an average spectral magnitude of background images;
• designating a region within the final saliency map as an object;
• classifying an object within the final saliency map;
• displaying the classification on a display device;
• causing an autonomous vehicle to perform a maneuver to avoid collision with the object;
• and
• wherein in filtering the pixel-value altered saliency map, salient edges within the pixel-value altered saliency map are blurred into salient regions.

A method for detecting salient objects in images, the method comprising acts of:

• mapping an input image into a frequency domain having a spectral magnitude;
• replacing the spectral magnitude with weights from a weight matrix W;
• transforming the frequency domain with the weights to a saliency map in the image domain, the saliency map having pixels with pixel values;
• performing a squaring operation on the saliency map by squaring the pixel values to generate a pixel-value altered saliency map such that all values in the pixel-value altered saliency map are nonnegative;
• generating a final saliency map by filtering the pixel-value altered saliency map;
• and
• generating the weight matrix W, such that the weight matrix W is a foreground weight matrix F divided by the background weight matrix B, wherein the foreground weight matrix F is an average spectral magnitude of foreground regions from a training set, and wherein the background weight matrix B is an average spectral magnitude of background images.

A method for detecting salient objects in images, the method comprising acts of:

• mapping an input image into a frequency domain having a spectral magnitude;
• replacing the spectral magnitude with weights from a weight matrix W;
• transforming the frequency domain with the weights to a saliency map in the image domain, the saliency map having pixels with pixel values;
• performing a squaring operation on the saliency map by squaring the pixel values to generate a pixel-value altered saliency map such that all values in the pixel-value altered saliency map are nonnegative;
• generating a final saliency map by filtering the pixel-value altered saliency map;
• generating the weight matrix W, such that the weight matrix W is a foreground weight matrix F divided by the background weight matrix B, wherein the foreground weight matrix F is an average spectral magnitude of foreground regions from a training set, and wherein the background weight matrix B is an average spectral magnitude of background images;
• designating a region within the final saliency map as an object;
• classifying an object within the final saliency map;
• displaying the classification on a display device;
• causing an autonomous vehicle to perform a maneuver to avoid collision with the object;
• and
• wherein in filtering the pixel-value altered saliency map, salient edges within the pixel-value altered saliency map are blurred into salient regions.