Object detection using cascaded convolutional neural networks

A cascaded convolutional neural networks object detection system comprising:

• an image access module configured to obtain an image;
• a first cascade layer comprising a first convolutional neural network, the first cascade layer configured to analyze multiple candidate windows identified in the image to identify a first set of the multiple candidate windows that include an object, each candidate window including a group of pixels of the image, the multiple candidate windows including overlapping candidate windows;
• a second cascade layer comprising a second convolutional neural network, the second cascade layer configured to analyze the first set of the multiple candidate windows to identify a second set of the multiple candidate windows that include an object;
• a third cascade layer comprising a third convolutional neural network, the third cascade layer configured to analyze the second set of the multiple candidate windows to identify a third set of the multiple candidate windows that include an object, the first cascade layer analyzing lower resolution versions of the ones of the multiple candidate windows identified by the second cascade layer as including an object than versions analyzed by the third cascade layer;
• and
• an output module configured to output, for each candidate window of the third set of the multiple candidate windows, an indication of the object included in the candidate window.

A computing device comprising:

• one or more processors;
• and
• one or more computer-readable storage media having stored thereon multiple instructions that, when executed by the one or more processors, cause the one or more processors to perform acts comprising:
• identifying multiple candidate windows in an image, each candidate window including a group of pixels of the image, the multiple candidate windows including overlapping candidate windows;
• identifying one or more of the multiple candidate windows that include an object, the identifying including analyzing the multiple candidate windows using cascaded convolutional neural networks, the cascaded convolutional neural networks including multiple cascade layers, each cascade layer comprising a convolutional neural network, the multiple cascade layers including a first cascade layer that analyzes the identified multiple candidate windows, a second cascade layer that analyzes ones of the multiple candidate windows identified by the first cascade layer as including an object, and a third cascade layer that analyzes ones of the multiple candidate windows identified by the second cascade layer as including an object, the third cascade layer analyzing higher resolution versions of the ones of the multiple candidate windows identified by the second cascade layer as including an object than versions analyzed by the first cascade layer;
• and
• outputting, as an indication of one or more objects in the image, an indication of one or more of the multiple candidate windows identified by the third cascade layer as including an object.