Canon Kabushiki Kaisha

Seikagaku Corporation

Honda Motor Co., Ltd.

Google Inc.

Nec C Orporation

Sensetime Group Limited

Yuji Kaneda

Masakazu Matsugu

Katsuhiko Mori

Takashi Suzuki

Yusuke Mitarai

Atsuo Nomoto

Shunsuke Nakano

Kotaro Yano

Masami Kato

Takahisa Yamamoto

Daisuke Nishino

Takashi Takata

Yoshinori Ito

Tadashi Hayashi

Kan Torii

Keisuke Oka

Shoji Kitagawa

Yuji Yasui

Hiroshi Sato

Hiroyuki Uchiyama

Yohei Kitahara

Atsushi Kawamura

Kiyoshi Suzuki

Xiaogang Wang

Hideo Noro

Satoshi Yashiro

Kiyotaka Takahashi

Tokitomo Ariyoshi

Junjie Yan

Kazuyo Ikeda

Naotsugu Sagawa

Masami Iida

Amir Najmi

Yasuji Saito

Xingyu Zeng

Yuhi Goto

Yingjie Cai

Shinan Liu

Naoko Kajimoto

Miwa Sawa

Naoko Kunii

Adam Jacob Prins

Kiyoshi Keyakidaidanchi 2-510 Suzuki

A driving assistance device is configured to: refer to an output of a detection device for detecting that an object is located in front of a vehicle; execute one or both of instructing a brake device of the vehicle to stop the vehicle and instructing a steering device of the vehicle to avoid a collision with the object by steering when an indicator value is less than a first threshold; execute a first preliminary operation when the indicator value is less than a second threshold; execute a second preliminary operation when the indicator value is less than a third threshold and it is determined that there is no travel path along which the vehicle is able to travel on both lateral sides of the object.

Driving assistance device, driving assistance method, and storage medium

At least one processor executes one or both of a braking control process of stopping a vehicle, and a steering-based avoidance control process of avoiding a collision with the object, execute a first preliminary operation control process of performing a first preliminary operation of notifying a driver that the object is present; and execute a second preliminary operation control process of performing a second preliminary operation of notifying the driver that the object is present when the indicator value is less than a third threshold and there is no travel path along which the vehicle is able to travel after the vehicle avoids the collision with the object in the steering. Control content is changed in accordance with a type of the object in at least some of the steering-based avoidance control process, the first preliminary operation control process, and the second preliminary operation control process.

A 3D object detection method includes: obtaining two-dimensional (2D) coordinates of at least one predetermined key point of a target object in an image to be processed; constructing a pseudo 3D detection body of the target object in a 2D space according to the 2D coordinates of the at least one predetermined key point; obtaining depth information of a plurality of vertices of the pseudo 3D detection body; and determining a 3D detection body of the target object in a 3D space according to the depth information of the plurality of vertices of the pseudo 3D detection body.

Three-dimensional object detection method and device, method and device for controlling smart driving, medium and apparatus

An information processing apparatus includes an extraction unit that extracts a feature from an image including a face, a first estimation unit that estimates a likelihood of the face with respect to each generation based on the feature, a storage unit that stores a plurality of samples, the plurality of samples each including a generation-specific combination of likelihoods and a correct age as a pair, a selection unit that selects a sample from the storage unit based on a combination of likelihoods estimated by the first estimation unit, and a second estimation unit that estimates an estimated age of the face and an error range thereof based on the sample selected by the selection unit.

Information processing apparatus for estimating age and method thereof

A first analysis unit () acquires second image data. The second image data is generated by compressing first image data by a predetermined encoding method. Further, the first analysis unit () performs image analysis of the acquired second image data to detect second image data satisfying a first predetermined condition. A decoding unit () decodes second image data detected by the first analysis unit () into third image data having higher resolution than that of the second image data. In the second analysis (), the image analysis of the third image data is performed.

Information processing apparatus, information processing system, control method, and program

An identification apparatus includes an acquisition unit configured to acquire input data and an identification unit configured to identify a class to which the acquired input data belongs based on a classifier configured to identify a class to which the data belongs from among a plurality of classes that includes two or more classes having been set beforehand.

Image identification apparatus and image identification method

An image processing apparatus includes an imaging unit, a determination unit, and a discrimination unit. The imaging unit images a target object using signals in a predetermined wavelength band in which a spectral transmittance of a specific substance of a plurality of substances on a surface of the target object is different from a spectral transmittance of the other substances of the plurality of substances. The determination unit determines a distribution state of the specific substance on the surface of the target object based on an image captured by the imaging unit. The discrimination unit discriminates a class to which the target object belongs based on the distribution state of the specific substance.

Image processing apparatus which determines category to which object in image belongs, method therefor, and object discrimination apparatus

An image processing apparatus stores, as instance images, a plurality of face images obtained by photographing respective faces of a plurality of persons on a plurality of photographing conditions, while associating the persons with the photographing conditions for each part; obtains the photographing condition of the input face image; approximates the respective parts of the input face images, by a combination of the instance images of the plurality of persons stored in association with the parts and the obtained photographing conditions; decides, for each part of the input face image, a combination corresponding to the combination in the approximation from the instance images of the plurality of persons stored in association with the part and a predetermined photographing condition; and generates an image obtained by photographing the input face image on the predetermined photographing condition, by synthesizing the obtained combination on the whole input face image.

Image processing apparatus and method of generating face image

An image processing apparatus comprises a detecting unit which detects an object from an input image, an extracting unit which extracts a feature amount of the object detected by the detecting unit, a similarity calculating unit which, in a case where a plurality of objects have been detected from the same input image by the detecting unit, calculates a degree of similarity of feature amounts of the plurality of objects, and an adjusting unit which adjusts a collating method of collating the plurality of objects based on respective feature amounts, on the basis of the degree of similarity calculated by the similarity calculating unit.

Image processing apparatus and method for collating a plurality of images

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.

Image retrieving apparatus and method

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.

Apparatus and method for estimating gazed position of person

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.

Apparatus and method of collating categories of images

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.

Object discriminating apparatus and method

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.

Selecting content using query-independent scores of query segments

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.

Image processing apparatus and image processing method of identifying object in image

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Kawasaki, Japan

Yuji Kaneda