Adobe, Inc.

Other

Max Gray Edell

Xuejun Xu

David Eldridge Benge

Gavin Stuart Peter Miller

John Bevil Bates

Matthew Keith Albright

Morgan David De Lossy

A licensing system and related methods are described utilizing aspects of distributed ledger technologies to facilitate trusted and verifiable licensing transactions for creative works. A client device can include an asset editing tool for incorporating an asset selected from a plurality of licensable assets into a new creative work. The selected asset can be downloaded for incorporation into the new creative work. The new creative work incorporating the selected asset can be analyzed to determine an amount that the selected asset contributed to the new creative work, or an amount that the new creative work is attributable to the selected asset. Based on the analysis, a smart contract associated with the new creative work can be generated to include license fees for licensing the new creative work, receive payment transactions for licensing the new creative work, and fairly disperse calculated portions of received payment transactions to a licensor of the new creative work and to another licensor of the incorporated selected asset.

Trusted transaction system for digital asset licensing

Embodiments provide traceability of edits to a document, i.e., a verifiable and immutable provenance chain for the document. Systems and methods enable traceability of edits, by encoding, for states of the document, a fingerprint (e.g., a cryptographic hash of the document's contents) and an edit history within a block written to a distributed ledger (e.g., a blockchain). The ledger is maintained via a self-organizing peer-to-peer distributed ledger network. Once added to the ledger, the contents of a block (e.g., the document's fingerprint and edit history) are immutable and the integrity of the edit history encoded in the ledger is secure. The algorithm that generates the fingerprint is sensitive to edits of the document. The non-corruptible fingerprint encoded in the ledger is employable to detect any edits that are not included in the encoded edit history and/or inconsistent with a currently available version of the document.

Traceability of edits to digital documents via distributed ledgers

Methods and systems are provided for training a neural network to track viewer engagement with a non-interactive display. Sensor data is obtained from one or more sensors, such as cameras, associated with a display device, and once a face is detected within the sensor data, a display sequence is initiated. The display sequence includes at least a first frame with a first visual feature and a second frame with a second visual feature. Using the sensor data obtained during presentation of the display sequence, viewer engagement with the sequence is tracked by determining eye movements and/or head movements. The detected eye movement and/or head movement is used to determine whether the person was actively engaged with the display sequence.

Training a neural network to track viewer engagement with non-interactive displays

In implementations of opting-in or opting-out of visual tracking, a computing device maintains digital images received for scanning, and includes an image scanning system that receives a digital image depicting one or more faces of persons captured in the digital image. The image scanning system is implemented to detect a face of a person who is depicted in the digital image from a scan of the digital image. The image scanning system can then scan the digital image for a visual tracking identifier that indicates a preference of the person for one of opting-in or opting-out of visual tracking. The image scanning system can detect the visual tracking identifier associated with the person from the scan of the digital image, and continue or discontinue the visual tracking of the person based on the visual tracking identifier indicating that the person opt-in or opts-out of visual tracking.

Opting-in or opting-out of visual tracking

Methods and systems are provided for tracking viewer engagement with a non-interactive display. Sensor data is obtained from one or more sensors, such as cameras, associated with a display device, and once a face is detected within the sensor data, a display sequence is initiated. The display sequence includes at least a first frame with a first visual feature and a second frame with a second visual feature. Using the sensor data obtained during presentation of the display sequence, viewer engagement with the sequence is tracked by determining eye movements and/or head movements. The detected eye movement and/or head movement is used to determine whether the person was actively engaged with the display sequence.

Growing community of inventors

Ottawa, Canada

Max Gray Edell