1. An image recognition device, comprising: a plurality of first charge storage circuits that store signal charges generated by photoelectric conversion sections provided in each of a plurality of pixels arranged in a two-dimensional matrix; a plurality of second charge storage circuits that store the signal charges generated by the photoelectric conversion sections provided in predetermined pixels of the plurality of pixels; a first charge read circuit section that reads a pixel signal corresponding to the signal charge stored in each of the first charge storage circuits and outputs an image according to the read pixel signal as a first image; a second charge read circuit section that reads a pixel signal corresponding to the signal charge stored in each of the second charge storage circuits and outputs an image according to the read pixel signal as a second image having a predetermined reduced number of pixels; a read circuit selection section that selects one of the first charge read circuit section and the second charge read circuit section as a charge read circuit section that reads an image; an image reading section that reads an image from the charge read circuit section selected by the read circuit selection section; and a feature amount determination section that calculates a feature amount of a subject included in the image read by the image reading section and determines a detection target subject according to the calculated feature amount, wherein the feature amount determination section determines the detection target subject according to a feature amount of each subject included in the second image read from the selected second charge read circuit section at first, and whether to select the first charge read circuit section and perform the determination for a subject included in the first image read from the selected first charge read circuit section is determined based on the determination result, wherein the feature amount determination section includes a feature amount calculation section that calculates the feature amount of each subject included in the image read by the image reading section, a classifier applying section that inputs the feature amount calculated by the feature amount calculation section to a classifier prepared in advance and outputs a classification score indicating a detection target subject likeliness, and a detection determination section that determines whether or not a subject expressed by the feature amount calculated by the feature amount calculation section is the detection target subject according to the classification score calculated by the classifier applying section, and wherein the feature amount calculation section calculates the feature amount of each subject, which is included in the second image read first by the image reading section, and the feature amount of each subject, which is included in the first image read next by the image reading section, using different calculation methods, and the classifier applying section inputs the feature amount calculated for the second image and the feature amount calculated for the first image to different classifiers prepared in advance.