Amazon Technologies, Inc.

Dmitri Veikherman

Dilip Kumar

Gerard Guy Medioni

George Leifman

Manoj Aggarwal

Korwin Jon Smith

Ehud Benyamin Rivlin

Yacov Hel-Or

Natan Peterfreund

Eli Osherovich

Sora Kim

Nikolai Orlov

Described is a multiple-camera system and process for detecting, tracking, and re-verifying agents within a materials handling facility. In one implementation, a plurality of feature vectors may be generated for an agent and maintained as an agent model representative of the agent. When the object being tracked as the agent is to be re-verified, feature vectors representative of the object are generated and stored as a probe agent model. Feature vectors of the probe agent model are compared with corresponding feature vectors of candidate agent models for agents located in the materials handling facility. Based on the similarity scores, the agent may be re-verified, it may be determined that identifiers used for objects tracked as representative of the agents have been flipped, and/or to determine that tracking of the object representing the agent has been dropped.

Agent re-verification and resolution using imaging

An identification system includes one or more infrared light sources and a camera that acquires images of a user's palm. For example, at a first time, one or more first images may be acquired by the camera using infrared light with a first polarization that represent external characteristics of the user's palm. At a second time, one or more second images may be acquired using infrared light with a second polarization that represent internal characteristics of the user's palm. These images are processed to determine a first set of feature vectors and a second set of feature vectors. A current signature may be determined using the first set of feature vectors and the second set of feature vectors. In addition, a user may be identified based on a comparison of the current signature and previously stored reference signatures that are associated with candidate user identifiers.

User identification system using infrared images of palm characteristics

This disclosure describes techniques for identifying users that are enrolled for use of a user-recognition system. To be identified using the user-recognition system, a user may first enroll in the system by stating an utterance at a first device having a first microphone. In response, the first microphone may generate first audio data. Later, when the user would like to be identified by the system, the user may state the utterance again, although this time to a second device having a second microphone. This second microphone may accordingly generate second audio data. Because the acoustic response of the first microphone may differ from the acoustic response of the second microphone, however, this disclosure describes techniques to apply a relative transfer function to one or both of the first or second audio data prior to comparing these data so as to increase the recognition accuracy of the system.

Utilizing sensor data for automated user identification

A non-contact biometric identification system includes a hand scanner that generates images of a user's palm. Images are acquired using light of a first polarization at a first time that show surface characteristics such as wrinkles in the palm while images acquired using light of a second polarization at a second time show deeper characteristics such as veins. Within the images, the palm is identified and subdivided into sub-images. The sub-images are subsequently processed to determine feature vectors present in each sub-image. A current signature is determined using the feature vectors. A user may be identified based on a comparison of the current signature with a previously stored reference signature that is associated with a user identifier.

Non-contact biometric identification system

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Nesher, Israel

Dmitri Veikherman