公开(公告)号：US09495591B2

公开(公告)日：2016-11-15

申请号：US13664295

申请日：2012-10-30

Applicant: QUALCOMM Incorporated

Inventor： Erik Visser ,  Haiyin Wang ,  Hasib A. Siddiqui ,  Lae-Hoon Kim

IPC: H04R3/00 ,  G06K9/00 ,  G06K9/62 ,  G06K9/32 ,  G06K9/46 ,  H04S7/00 ,  G06T7/20

CPC classification number: G06K9/00624 ,  G06K9/00 ,  G06K9/0063 ,  G06K9/3233 ,  G06K9/4628 ,  G06K9/4671 ,  G06K9/6293 ,  G06T7/20 ,  H04R3/00 ,  H04R3/005 ,  H04S7/30 ,  H04S2400/11 ,  H04S2400/15

Abstract: Methods, systems and articles of manufacture for recognizing and locating one or more objects in a scene are disclosed. An image and/or video of the scene are captured. Using audio recorded at the scene, an object search of the captured scene is narrowed down. For example, the direction of arrival (DOA) of a sound can be determined and used to limit the search area in a captured image/video. In another example, keypoint signatures may be selected based on types of sounds identified in the recorded audio. A keypoint signature corresponds to a particular object that the system is configured to recognize. Objects in the scene may then be recognized using a shift invariant feature transform (SIFT) analysis comparing keypoints identified in the captured scene to the selected keypoint signatures.

Abstract translation: 公开了用于识别和定位场景中的一个或多个物体的方法，系统和制品。 拍摄场景的图像和/或视频。 使用在场景录制的音频，捕获的场景的对象搜索变窄。 例如，可以确定声音的到达方向（DOA）并用于限制捕获的图像/视频中的搜索区域。 在另一示例中，可以基于记录的音频中识别的声音的类型来选择关键点签名。 关键点签名对应于系统配置为识别的特定对象。 然后可以使用移位不变特征变换（SIFT）分析来比较场景中的对象，比较在捕获的场景中识别的关键点与所选择的关键点签名。

公开(公告)号：US20130272548A1

公开(公告)日：2013-10-17

申请号：US13664295

申请日：2012-10-30

Applicant: QUALCOMM INCORPORATED

Inventor： Erik Visser ,  Haiyin Wang ,  Hasib A. Siddiqui ,  Lae-Hoon Kim

IPC: G06K9/00 ,  H04R3/00

CPC classification number: G06K9/00624 ,  G06K9/00 ,  G06K9/0063 ,  G06K9/3233 ,  G06K9/4628 ,  G06K9/4671 ,  G06K9/6293 ,  G06T7/20 ,  H04R3/00 ,  H04R3/005 ,  H04S7/30 ,  H04S2400/11 ,  H04S2400/15

Abstract: Methods, systems and articles of manufacture for recognizing and locating one or more objects in a scene are disclosed. An image and/or video of the scene are captured. Using audio recorded at the scene, an object search of the captured scene is narrowed down. For example, the direction of arrival (DOA) of a sound can be determined and used to limit the search area in a captured image/video. In another example, keypoint signatures may be selected based on types of sounds identified in the recorded audio. A keypoint signature corresponds to a particular object that the system is configured to recognize. Objects in the scene may then be recognized using a shift invariant feature transform (SIFT) analysis comparing keypoints identified in the captured scene to the selected keypoint signatures.

Abstract translation: 公开了用于识别和定位场景中的一个或多个物体的方法，系统和制品。 拍摄场景的图像和/或视频。 使用在场景录制的音频，捕获的场景的对象搜索变窄。 例如，可以确定声音的到达方向（DOA）并用于限制捕获的图像/视频中的搜索区域。 在另一示例中，可以基于记录的音频中识别的声音的类型来选择关键点签名。 关键点签名对应于系统配置为识别的特定对象。 然后可以使用移位不变特征变换（SIFT）分析来比较场景中的对象，比较在捕获的场景中识别的关键点与所选择的关键点签名。