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公开(公告)号:US20180308253A1
公开(公告)日:2018-10-25
申请号:US15665222
申请日:2017-07-31
Inventor: Hyun Surk RYU , Joo Yeon WOO , Keun Joo PARK , Hyun Ku LEE , Wei Heng LIU , Dong Qing ZOU , Feng SHI , Jia LI , Qiang WANG
CPC classification number: G06T7/80 , G06K9/00711 , G06K9/209 , G06K9/78 , G06K2009/00738 , G06T7/248 , G06T7/292 , G06T2207/10016 , G06T2207/10028 , H04N5/04
Abstract: Methods and apparatuses for time alignment calibration are provided including acquiring an event-stream and video images of a target object which are simultaneously shot by a dynamic vision sensor and an assistant vision sensor, determining a key frame that reflects obvious movement of the target object from the video images, mapping effective pixel positions of the target object in the key frame and effective pixel positions of the target object in the neighboring frames according to a spatial relative relation between the dynamic vision sensor and the assistant vision sensor, determining a first target object template that covers events in a first event-stream segment from the plurality of target object templates, and using a time alignment relation of an intermediate instant of the first event-stream segment and a timestamp of a frame corresponding to the first target object template between the dynamic vision sensor and the assistant vision sensor.
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公开(公告)号:US20180137673A1
公开(公告)日:2018-05-17
申请号:US15811200
申请日:2017-11-13
Inventor: Feng SHI , Dong Qing ZOU , Wei Heng LIU , De Heng QIAN , Hyun Surk RYU , Jia LI , Jing Tao XU , Kyoobin LEE , Qiang WANG
CPC classification number: G06T15/20 , G06K9/605 , G06K9/6202 , G06K2009/00738 , G06T15/04 , G06T2207/10028 , G06T2207/20208 , G06T2207/30244
Abstract: Embodiments of the present invention provide a method and device for processing Dynamic Vision Sensor (DVS) events. The method comprises the operations of: acquiring a DVS event map sequence; for any DVS event map in the DVS event map sequence, extracting a DVS event feature descriptor, where the DVS event feature descriptor has a scale-invariant feature and/or a rotation-invariant feature; determining, according to the extracted DVS event feature descriptor, a three-dimensional space pose of the DVS event map at the current moment; and, generating, according to the three-dimensional space pose of each DVS event map, a DVS event map sequence with temporal consistency. The embodiments of the present invention are used for generating, from a DVS event map sequence, a DVS event map sequence with temporal consistency.
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公开(公告)号:US20180137647A1
公开(公告)日:2018-05-17
申请号:US15813668
申请日:2017-11-15
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Jia LI , Qiang WANG , Feng SHI , Deheng QIAN , Dongqing ZOU , Hyunsurk Eric RYU , JinMan PARK , Jingtao XU , Keun Joo PARK , Weiheng LIU
CPC classification number: G06T7/73 , G06K9/00805 , G06K9/4628 , G06K9/4671 , G06K9/6274 , G06K9/66 , G06N3/0445 , G06T7/11 , G06T2210/12
Abstract: The disclosure provides an object detection method and apparatus based on a Dynamic Vision Sensor (DVS). The method includes the following operations of: acquiring a plurality of image frames by a DVS; and, detecting the image frames by a recurrent coherent network to acquire a candidate box for objects to be detected, wherein the recurrent coherent network comprising a frame detection network model and a candidate graph model. By using a new recurrent coherent detection network, a bounding box for an object to be detected is fast detected from the data acquired by a DVS. The detection speed is improved greatly while ensuring the detection accuracy.
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公开(公告)号:US20180137639A1
公开(公告)日:2018-05-17
申请号:US15812554
申请日:2017-11-14
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Dongqing ZOU , Feng SHI , Weiheng LIU , Deheng QIAN , Hyunsurk Eric RYU , Jia LI , Jingtao XU , Keun Joo PARK , Qiang WANG , Changwoo SHIN
CPC classification number: G06T7/593 , G06T2207/10012 , G06T2207/10028 , H04N13/128 , H04N13/239 , H04N2013/0081
Abstract: Exemplary embodiments provide an image vision processing method, device and equipment and relate to: determining parallax and depth information of event pixel points in a dual-camera frame image acquired by Dynamic Vision Sensors; determining multiple neighboring event pixel points of each non-event pixel point in the dual-camera frame image; determining, according to location information of each neighboring event pixel point of each non-event pixel point, depth information of the non-event pixel point; and performing processing according to the depth information of each pixel point in the dual-camera frame image. Since non-event pixel points are not required to participate in the matching of pixel points, even if it is difficult to distinguish between the non-event pixel points or the non-event pixel points are occluded, depth information of the non-event pixel points can be accurately determined according to the location information of neighboring event pixel points.
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