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公开(公告)号:US09607215B1
公开(公告)日:2017-03-28
申请号:US14495629
申请日:2014-09-24
Applicant: Amazon Technologies, Inc.
Inventor: Manika Puri
IPC: G06K9/00
CPC classification number: G06K9/00355 , G06K2209/40
Abstract: Techniques are described for detecting the presence and positions of fingers using depth information. For each of multiple target points represented by a depth image, an evaluation is performed using a region of points surrounding the pixel. The region has an inner zone and side zones. Multiple iterations are performed for each target pixel, with different sizes and orientations of the region being used in the different iterations. An average depth and an average surface normal direction are determined for each zone. The average depth and average surface normal direction of the inner zone are compared to the average depths and the average surface normal directions of the side zones to determine whether the target pixel is part of a finger.
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公开(公告)号:US09740924B1
公开(公告)日:2017-08-22
申请号:US14498160
申请日:2014-09-26
Applicant: Amazon Technologies, Inc.
Inventor: Sowmya Gopalan , Manika Puri
CPC classification number: G06K9/00389 , G06K9/00536 , G06K9/4604 , G06K9/4642 , G06K9/4647 , G06K9/48
Abstract: In order to classify the presented pose of a human hand, a feature distribution map of the pose is compared to reference feature distribution maps. To generate a feature distribution map, each contour point of a hand is analyzed to determine a corresponding feature set. The feature set of a contour point includes a distance feature and an angle feature of the contour point in relation to one of its neighboring contour points. The feature sets generated from an observed pose are compared to feature sets of reference poses to determine which of the reference poses most closely matches the presented pose.
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公开(公告)号:US10769442B1
公开(公告)日:2020-09-08
申请号:US15700536
申请日:2017-09-11
Applicant: Amazon Technologies, Inc.
Inventor: Siyi Ding , Xiaoran Wang , Manika Puri , Mashhour Solh , Philip James Taylor
Abstract: Techniques are generally described for scene change detection. A first and second histogram representing frames of a video may be received. A Euclidean distance between the first and second histogram may be determined. A third histogram of a third frame may be received. Values of the third histogram may be compared to corresponding values of a background model of the environment. A fourth frame and a fifth frame of image data of the video may be received. A flow value between a first block of pixels of the fourth frame and a corresponding second block of pixels of the fifth frame may be determined. The flow value may be determined based on a motion vector and a sum of absolute differences between the first and second block. A portion of the video may be streamed to a remote computing device if the flow value exceeds a threshold value.
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公开(公告)号:US09753119B1
公开(公告)日:2017-09-05
申请号:US14167813
申请日:2014-01-29
Applicant: Amazon Technologies, Inc.
Inventor: Kavitha Velusamy , Ning Yao , Wai Chung Chu , Sowmya Gopalan , Qiang Liu , Rahul Agrawal , Manika Puri
IPC: G01S5/20
CPC classification number: G01S5/20 , G01S5/18 , G01S5/22 , G01S17/023 , G01S17/36 , G01S17/42 , G01S17/46 , G01S17/89
Abstract: A system may utilize sound localization techniques, such as time-difference-of-arrival techniques, to estimate an audio-based sound source position from which a sound originates. An optical image or depth map of an area containing the sound source location may then captured and analyzed to detect an object that is known or expected to have produced the sound. The position of the object may also be determined based on the analysis of the optical image or depth map. The position of the sound source may then be determined based at least in part on the position of the detected object or on a combination of the audio-based sound source position and the determined position of the object.
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公开(公告)号:US09607207B1
公开(公告)日:2017-03-28
申请号:US14231191
申请日:2014-03-31
Applicant: Amazon Technologies, Inc.
Inventor: Manika Puri
IPC: G06K9/00
CPC classification number: G06K9/00201
Abstract: Techniques are described for determining edge pixels from a depth map in order to identify edges of an object within an environment. The techniques may fit a plane to a group of pixels comprising a subject pixel and neighbors of the subject pixel. Each pixel of the group may then be classified as either an inlier pixel or an outlier pixel, and a ratio of inlier pixels to outlier pixels of the group may be calculated. The techniques then compare this ratio to a threshold ratio to designate the subject pixel as either an edge pixel or a non-edge pixel. Edge pixels designated in this manner may then be used to identify object edges and, hence, objects in the environment.
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