Abstract: An image processing apparatus comprises: a detecting unit to detect, respectively from plural images obtained by imaging with plural imaging units a space in which plural persons exist, positions of the persons on the images; an associating unit to perform association of a same person in the plural images; a person position estimating unit to estimate positions of the persons in the space, based on the positions of the persons on the images detected from the plural images and a result of the association by the associating unit; a direction estimating unit to estimate eye directions of the persons, based on the plural images; and a distribution estimating unit to estimate a spatial distribution of positions gazed by the plural persons, based on the estimated positions of the plural persons in the space and the estimated eye directions of the plural persons.

Abstract: A line-of-sight detection apparatus is configured to calculate a mean luminance value in an eye area of a face image, determine that an object is a person whose iris area is blue or green in a case in which the calculated mean luminance value is equal to or greater than a predetermined value, determine a correction parameter for correcting the eye area based on the determined color of the iris area, and generate a luminance image in which the eye area is corrected by using the determined correction parameter. Thus, the line-of-sight detection apparatus detects a line of sight with high accuracy regardless of the color of the iris area.

Abstract: An image retrieving apparatus is equipped with: an image obtaining unit for obtaining a plurality of images; a category obtaining unit for obtaining a category to which each of the obtained images belongs; a basic searching unit, for searching a specific image including a specific object, from the obtained images; a counting unit for counting the number of the specific images for each category obtained; a determining unit for determining whether or not an additional search for the specific image is necessary for each category, based on the counted number of the specific images of each category; and an additional searching unit for searching the specific image from among the images which belong to the category for which it has been determined that the additional search is necessary and from which the searched specific image has been excluded.

Abstract: Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a method for responding to queries. A first user query is received. The first user query is processed including identifying one or more segments in the first user query, a segment representing a word or a phrase. A stand-alone score is determined for each segment of the first user query, wherein the stand-alone score is an indication of a likelihood that the segment represents a stand-alone query and that the segment represents a main topic of the first user query. A historical log of queries is processed to determine query-independent scores for segments that are included in queries represented by the log. The final query-independent scores are used to determine the stand-alone score for each segment of the first query.

Abstract: A facial expression recognition apparatus (10) detects a face image of a person from an input image, calculates a facial expression evaluation value corresponding to each facial expression from the detected face image, updates, based on the face image, the relationship between the calculated facial expression evaluation value and a threshold for determining a facial expression set for the facial expression evaluation value, and determines the facial expression of the face image based on the updated relationship between the facial expression evaluation value and the threshold for determining a facial expression.

Abstract: An image processing apparatus includes: a holding unit that holds a plurality of images; a condition checking unit that checks imaging conditions of the plurality of images; a collation determining unit that determines whether to collate images among the plurality of images based on the imaging conditions of the images; a collation unit that collates the images determined to be collated by the collation determining unit to obtain a degree of similarity; and a classifying unit that classifies the collated images into a same category when the degree of similarity is equal to or greater than a predetermined threshold.

Abstract: The image processing apparatus detects a region of a subject from an input image, and extracts an image feature amount from the region. Also, the apparatus classifies the subject into any one of plural attributes based on the image feature amount, and estimates, based on the image feature amount and an attribute into which it is classified, an attribute value of the subject belonging to the attribute into which it is classified.

Abstract: A facial expression recognition apparatus (10) detects a face image of a person from an input image, calculates a facial expression evaluation value corresponding to each facial expression from the detected face image, updates, based on the face image, the relationship between the calculated facial expression evaluation value and a threshold for determining a facial expression set for the facial expression evaluation value, and determines the facial expression of the face image based on the updated relationship between the facial expression evaluation value and the threshold for determining a facial expression.

Abstract: An object discriminating apparatus is provided with an obtaining unit configured to obtain an input image including an object; an extracting unit configured to extract a feature from the input image; a calculating unit configured to calculate, by collating the feature extracted from the input image and a feature of a previously registered registration image with each other, similarity between the object included in the input image and an object included in the registration image; a deriving unit configured to derive a difference between a variation in the input image and a variation in an output image; a converting unit configured to convert the calculated similarity on the basis of the derived difference between the variations; and a deciding unit configured to decide, on the basis of the converted similarity, whether or not the object included in the input image is identical with the object included in the registration image.

Abstract: A facial expression recognition apparatus (10) detects a face image of a person from an input image, calculates a facial expression evaluation value corresponding to each facial expression from the detected face image, updates, based on the face image, the relationship between the calculated facial expression evaluation value and a threshold for determining a facial expression set for the facial expression evaluation value, and determines the facial expression of the face image based on the updated relationship between the facial expression evaluation value and the threshold for determining a facial expression.

Abstract: The degree of similarity between corresponding local feature amounts out of a plurality of local feature amounts of the object in the input image and a plurality of local feature amounts of an object in an image registered in advance is obtained. At least one degree of similarity is selected out of the obtained degrees of similarity based on a capturing condition for the object in the input image and a capturing condition for the object in the registered image, and one degree of similarity is derived from the at least one selected degree of similarity. It is determined based on the one derived degree of similarity whether the object in the input image belongs to the same category as the object in the registered image.

Abstract: The present invention facilitates the setting of a condition for the execution of predetermined processing and enables the execution of processing conforming to a user's intention. In an image processing apparatus, a predetermined object is detected in an image selected based on an instruction from a user, a determination is made regarding an attribute of the detected object, and the determined attribute is set as an execution condition used when executing predetermined processing on an image.

Abstract: An image is obtained. At least one local region is set in the image. Feature patterns are extracted from the local region, and, out of a plurality of bins corresponding to a plurality of patterns which can form the feature patterns, bins that have been determined in accordance with a type of the local region are set as histogram bins used in generating a histogram. A histogram is generated corresponding to the extracted feature patterns using the set histogram bins, and image recognition is performed using the generated histogram.

Abstract: An image processing apparatus acquires a plurality of input images which are serially photographed, detects a plurality of object regions from each input image, and associates object regions in a past input image with object regions in a current input image. If any object region that has not been appropriately associated exists in the object regions detected from the past input image, the apparatus calculates object region movement information for each size of the object region based on the object regions mutually associated between the past input image and the current input image, and estimates a position of the object region of the current input image that has not been associated based on the movement information for each size of the object region and a size of the object region that has not been associated.

Abstract: An image including a face is input (S201), a plurality of local features are detected from the input image, a region of a face in the image is specified using the plurality of detected local features (S202), and an expression of the face is determined on the basis of differences between the detection results of the local features in the region of the face and detection results which are calculated in advance as references for respective local features in the region of the face (S204).

Abstract: A person is detected as a subject from an image obtained by image capture, and information, for example, the number of such subjects, is obtained as subject-related information. Then, the greater the number of subjects, the more a setting of a condition that the subjects should satisfy is relaxed. As a result, in an image processing apparatus having a function that identifies a subject state, the usability of that function that identifies the subjects can be improved even in a case in which multiple subjects are present.

Abstract: A line-of-sight detection apparatus includes a detection unit configured to detect a face from image data, a first extraction unit configured to extract a feature amount corresponding to a direction of the face from the image data, a calculation unit configured to calculate a line-of-sight reliability of each of a right eye and a left eye based on the face, a selection unit configured to select an eye according to the line-of-sight reliability, a second extraction unit configured to extract a feature amount of an eye region of the selected eye from the image data, and an estimation unit configured to estimate a line of sight of the face based on the feature amount corresponding to the face direction and the feature amount of the eye region.

Abstract: A line-of-sight detection apparatus is configured to calculate a mean luminance value in an eye area of a face image, determine that an object is a person whose iris area is blue or green in a case in which the calculated mean luminance value is equal to or greater than a predetermined value, determine a correction parameter for correcting the eye area based on the determined color of the iris area, and generate a luminance image in which the eye area is corrected by using the determined correction parameter. Thus, the line-of-sight detection apparatus detects a line of sight with high accuracy regardless of the color of the iris area.

Abstract: An information processing apparatus comprising: an obtaining unit configured to obtain image data; a detection unit configured to detect an object from the image data; an attribute determination unit configured to determine an attribute indicating a characteristic of the object detected by the detection unit; a registration unit configured to register the image data in at least one of a plurality of dictionaries based on the attribute determined by the attribute determination unit; and an adding unit configured to add, when the image data is registered in not less than two dictionaries, link information concerning the image data registered in the other dictionary to the image data registered in one dictionary.

Abstract: A facial expression recognition apparatus (10) detects a face image of a person from an input image, calculates a facial expression evaluation value corresponding to each facial expression from the detected face image, updates, based on the face image, the relationship between the calculated facial expression evaluation value and a threshold for determining a facial expression set for the facial expression evaluation value, and determines the facial expression of the face image based on the updated relationship between the facial expression evaluation value and the threshold for determining a facial expression.