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11.发明申请公开(公告)号：US20180350070A1
公开(公告)日：2018-12-06
申请号：US15989265
申请日：2018-05-25
Applicant: FUJITSU LIMITED
Inventor： Daisuke Ishii , Osafumi NAKAYAMA
CPC classification number: G06T7/0012 , G06F3/013 , G06K9/00604 , G06K9/4604 , G06K9/4652 , G06T7/62 , G06T7/70 , G06T7/73 , G06T2207/30041
Abstract: A recording medium storing a program causing a computer to execute: detecting an eye area of the eye; detecting bright spot areas in the eye area; setting a reference point in a pupa; setting a first search lines radially; determining whether each first search lines passes through the bright spot areas; determining, for a second search line that passes through the bright spot area, a degree of overlapping between the bright spot area and the pupil based on brightness on a circumference of the bright spot area; setting a search range for a point on a contour of the pupil based on the degree; detecting a first point on the contour; detecting, for a third search line that does not pass through the bright spot areas, a second point on the contour on the third search line; and detecting the pupil, based on the first and second points,
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12.发明申请公开(公告)号：US20180315259A1
公开(公告)日：2018-11-01
申请号：US15949910
申请日：2018-04-10
Applicant: FUJITSU LIMITED
Inventor： Osafumi NAKAYAMA
Abstract: A waveform estimating method performed by a computer, the waveform estimating method including: estimating a first vibration component of less than a first frequency in a period from a present time to a time preceding by a half wavelength of the first frequency, using an input waveform in the period, the input waveform corresponding to a driving trajectory of a vehicle traveling on a roadway; and calculating a second vibration component of the first frequency or higher in the period by subtracting the first vibration component from the input waveform.
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公开(公告)号：US20170032688A1
公开(公告)日：2017-02-02
申请号：US15157681
申请日：2016-05-18
Applicant: FUJITSU LIMITED
Inventor： Osafumi NAKAYAMA
CPC classification number: G09B19/167 , G06K9/00798 , G06T3/00 , G06T11/60 , G06T2207/10016 , G06T2207/20221 , G06T2207/30241 , G06T2207/30256 , G09B9/042
Abstract: A computer detects a virtual central line of a traveling lane from a road-captured image captured from a vehicle. Next, the computer displays a transformed image generated by transforming the road-captured image such that the detected virtual central line is situated in a prescribed position. At this point, the computer moves a display position of a symbol indicating the vehicle on the generated transformed image according to a result of detecting a traveling position of the vehicle in the traveling lane.
Abstract translation: 计算机从从车辆捕获的道路拍摄图像中检测行驶车道的虚拟中心线。 接下来，计算机显示通过转换道路拍摄图像而生成的变换图像，使得检测到的虚拟中心线位于规定位置。 此时，计算机根据检测行驶车道中的车辆的行驶位置的结果，将表示车辆的符号的显示位置移动到生成的变换图像上。
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14.发明公开公开(公告)号：US20230343080A1
公开(公告)日：2023-10-26
申请号：US18341548
申请日：2023-06-26
Applicant: Fujitsu Limited
Inventor： Junya FUJIMOTO , Osafumi NAKAYAMA
IPC: G06V10/778 , G06V40/20 , G06V10/84
CPC classification number: G06V10/7788 , G06V40/23 , G06V10/85
Abstract: A hidden semi-Markov model includes plural second hidden Markov models each containing plural first hidden Markov models using types of movement of a person as states. The plural second hidden Markov models each use partial actions that are parts of actions determined by combining plural movements as states. In the hidden semi-Markov model observation probabilities are leant for each type of the movements of the plural first hidden Markov models using unsupervised learning. The learnt observation probabilities are fixed, and input first supervised data is augmented to give second supervised data, and transition probabilities of the movements of the first hidden Markov models are learned by supervised learning in which the second supervised data is employed. The learnt observation probabilities and transition probabilities are employed to build the hidden semi-Markov model that is a model for estimating segments of the partial actions.
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公开(公告)号：US20230237690A1
公开(公告)日：2023-07-27
申请号：US18191034
申请日：2023-03-28
Applicant: FUJITSU LIMITED
Inventor： Masakiyo TANAKA , Osafumi NAKAYAMA , Yuichi MURASE , Chisato SHIODA
IPC: G06T7/70 , G06T7/20 , G06V10/25 , G06V10/762
CPC classification number: G06T7/70 , G06T7/20 , G06V10/25 , G06V10/762 , G06T2207/20044 , G06V2201/07
Abstract: An information processing device configured to: specify, from a moving image obtained by imaging work of a person, a first plurality of stationary positions at which the person is stationary and a movement order in which the person moves through the first plurality of stationary positions, divide the first plurality of stationary positions into a first plurality of clusters by clustering the first plurality of stationary positions, when a cluster included in the first plurality of clusters includes a pair of stationary positions with a relationship of a movement source and a movement destination in the movement order, divide a second plurality of stationary positions included in the cluster into a second plurality of clusters by clustering the second plurality of stationary positions, and generate a region of interest in the moving image based on the second plurality of clusters.
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Patent Agency Ranking
16.发明公开公开(公告)号：US20230206639A1
公开(公告)日：2023-06-29
申请号：US17946468
申请日：2022-09-16
Applicant: FUJITSU LIMITED
Inventor： Takuma YAMAMOTO , Yuya OBINATA , Osafumi NAKAYAMA
IPC: G06V20/52 , G06V20/40 , G06V40/20 , G06V10/776 , G06V40/16 , G06V10/75 , G06V10/86 , G06V10/40 , G06V10/82
CPC classification number: G06V20/52 , G06V20/41 , G06V40/20 , G06V10/776 , G06V40/174 , G06V10/751 , G06V10/86 , G06V10/40 , G06V10/82
Abstract: An information processing apparatus acquires video image data that includes target objects including a person and an object, and specifies, by using graph data that indicates a relationship between each of target objects stored in a storage unit, a relationship between each of the target objects included in the acquired video image data. The information processing apparatus specifies, by using a feature value of the person included in the acquired video image data, a behavior of the person included in the video image data. The information processing apparatus predicts, by inputting the specified behavior of the person and the specified relationship to a probability model, a future behavior or a future state of the person.
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17.发明申请公开(公告)号：US20190156512A1
公开(公告)日：2019-05-23
申请号：US16190389
申请日：2018-11-14
Applicant: FUJITSU LIMITED
Inventor： Tetsuhiro KATO , Osafumi NAKAYAMA
Abstract: A method for estimating orientation includes: executing a detection process that includes detecting multiple line segments from each of multiple images included in a video image captured by an imaging device; executing an estimation process that includes estimating a first inclination that is an inclination of a line segment that is among the multiple line segments and detected from a central region including a center of an image among the multiple images; and associating the first inclination with a vertical direction in a three-dimensional space to estimate an orientation of the imaging device.
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公开(公告)号：US20140362193A1
公开(公告)日：2014-12-11
申请号：US14291188
申请日：2014-05-30
Applicant: FUJITSU LIMITED
Inventor： Jun KANETAKE , Osafumi NAKAYAMA
CPC classification number: H04N13/221 , G01S1/00 , G01S5/16 , G01S11/12 , G06T7/579 , G06T2207/30252 , H04N2013/0081
Abstract: A processor of a distance measuring apparatus calculates a three-dimensional position of an object in the surroundings based on the first image, the second image and the amount of movement. The processor determines that calculated three-dimensional position is an error, when the displacement between a fourth position at which a third position set based on the calculated three-dimensional position of the object is projected on either one image of the first image and the second image and a position of the object in the one image is equal to or larger than a prescribed value. The processor makes the calculated three-dimensional position a distance measurement target when the calculated three-dimensional position is not determined as an error, and when determined as an error, excludes the calculated three-dimensional position from the distance measurement target.
Abstract translation: 距离测量装置的处理器基于第一图像，第二图像和移动量计算周围环境中的对象的三维位置。 处理器确定所计算的三维位置是错误，当基于所计算的对象的三维位置设置的第三位置的第四位置投影到第一图像的一个图像和第二图像之间的位移时， 图像和一个图像中的对象的位置等于或大于规定值。 当计算出的三维位置未被确定为误差时，处理器使得计算出的三维位置成为距离测量对象，并且当被确定为误差时，从距离测量目标排除所计算的三维位置。
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19.发明申请公开(公告)号：US20240428669A1
公开(公告)日：2024-12-26
申请号：US18670950
申请日：2024-05-22
Applicant: Fujitsu Limited
Inventor： Yasuhiro AOKI , Osafumi NAKAYAMA
Abstract: An information processing program causes a computer to execute a process including acquiring a video image captured by each of one or more camera devices, specifying, by analyzing the acquired video image, a relationship in which a behavior between a plurality of persons who are included in the video image has been identified, determining, based on the specified relationship, whether or not an abnormality has occurred between the plurality of persons outside the image capturing range of each of the camera devices, and when determining that the abnormality has occurred, outputting an alert.
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20.发明申请公开(公告)号：US20190191098A1
公开(公告)日：2019-06-20
申请号：US16210043
申请日：2018-12-05
Applicant: FUJITSU LIMITED
Inventor： Daisuke Ishii , Osafumi NAKAYAMA
CPC classification number: H04N5/23299 , G06T7/75 , H04N5/23218 , H04N7/181
Abstract: An object tracking apparatus is configured to execute a tracking process, a prediction process, an influence-degree obtaining process, and a difficulty-degree obtaining process, wherein the influence-degree obtaining process is configured to obtain a backside influence degree representing that a detection of an object to be tracked is affected by other object that overlaps the object, wherein the difficulty-degree obtaining process is configured to calculate, for each object to be tracked, a detection difficulty degree for detecting the object from each of next frames captured by respective cameras, based on the backside influence degree, wherein the tracking process is configured to select the next frame that is included in a set of next frames in a pieces of video and from which the object is to be detected, based on the detection difficulty degree, and detect the object from the selected next frames.
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