In one embodiment, a command is received from a video provider at a media rendering device, the command being a command to embed a subscriber ID in at least one video frame in a video stream. A random key, k is also received from the video provider at the media rendering device. An injective transformation is invoked for k and the subscriber ID, the injective transformation generating a sequence of pairs of: near-transparent patterns and corresponding time periods. Logical blocks of the at least one video frame in the video stream are overlaid with one of the near-transparent patterns for its one of the corresponding time periods. Related apparatus, systems, and methods are also described.

An optical code reader classifies a code depicted in input imagery, so that appropriate decoding actions can be invoked. This classification may identify, e.g., (a) whether the code is of a continuous tone or sparse mark variety, (b) which one of different reference signals it includes, and (c) which one of different protocols is used in expressing reference and payload signal components of the code. A great variety of other features and technologies are detailed as well.

A method is provided for watermarking a machine learning model used for object detection or image classification. In the method, a first subset of a labeled set of ML training samples is selected. The first subset is of a predetermined class of images. In one embodiment, the first pixel pattern is selected and sized to have substantially the same dimensions as each sample of the first subset or each bounding box in the case of an object detector. Each sample of the first subset is relabeled to have a different label than the original label. An opacity of the pixel pattern may be adjusted independently for different parts of the pattern. The ML model is trained with the labeled set of ML training samples and the first subset of relabeled ML training samples. Using multiple different opacity factors provides both reliability and credibility to the watermark.

A digital watermark analysis apparatus, comprising an image capturing unit for capturing a printed product where additional information is embedded by superimposing a pattern on an image to acquire a captured image, a calculation unit for calculating a spatial frequency characteristic of each small area in the captured image, a specifying unit for specifying an embedded signal strength and an embedding position of the additional information, a decision unit for deciding, based on the embedding position information and the embedded signal strength information, a position in the captured image of a marker detection area for detecting a marker as a reference position for acquiring the additional information, and an acquisition unit for detecting a marker in the marker detection area and acquiring the additional information in the captured image with reference to the detected marker.

Imagery captured by an autonomous robot is analyzed to discern digital watermark patterns. In some embodiments, identical but geometrically-inconsistent digital watermark patterns are discerned in an image frame, to aid in distinguishing multiple depicted instances of a particular item. In other embodiments, actions of the robot are controlled or altered in accordance with image processing performed by the robot on a digital watermark pattern. The technology is particularly described in the context of retail stores in which the watermark patterns are encoded, e.g., on product packaging, shelving, and shelf labels. A great variety of other features and arrangements are also detailed.

A phase estimation method estimates the phase of signal components using a point spread function. The method obtains a point spread function that expresses complex frequencies at a non integer location in terms of integral frequencies, for a complex frequency of a signal at a non integer location in a complex frequency domain. It obtains complex frequencies of the signal for the integral frequencies, and computes a sum of products of the complex frequencies of the signal at the integral frequencies with the corresponding complex values of the point spread function to provide an estimate of phase of the signal at the non integer location.

The present disclosure provides for methods, apparatus and computer readable media related to screen-capture communication based on invisible watermark. An aspect of the disclosure provides for a method including inserting one or more templates into one or more frames of a video for correcting frame perspective of the one or more frames captured by a device. The method further includes writing a message into the one or more frames of the video and displaying the video. According to a second aspect, a second method is provided. The second method includes capturing one or more frames of a video displayed on a device comprising a hidden message. The method further includes locating one or more templates and correcting frame perspective of the captured frames based on the templates. The method further includes extracting the message from the one or more frames of the video.

A system for generating and detecting watermarks within a video frame (e.g., video content) is described to determine whether a data interruption has occurred. In one or more implementations, the system includes a generation module communicatively coupled to a video source and a watermark detection module configured to receive a plurality of video watermarks. The watermarking detection module is configured to determine whether a watermark embedded in a current (e.g., a second) video frame is different from a watermark embedded in the previous (e.g., a first) video frame. The watermarking detection module is configured to generate an error signal when the watermark embedded in the current (e.g., a second) video frame is not different than the watermark embedded in the previous (e.g., a first) video frame to indicate a data interruption event has occurred.

Arrangements involving portable devices (e.g., smartphones and tablet computers) are disclosed. One arrangement enables a content creator to select software with which that creator's content should be rendered—assuring continuity between artistic intention and delivery. Another utilizes a device camera to identify nearby subjects, and take actions based thereon. Others rely on near field chip (RFID) identification of objects, or on identification of audio streams (e.g., music, voice). Some technologies concern improvements to the user interfaces associated with such devices. Others involve use of these devices in connection with shopping, text entry, sign language interpretation, and vision-based discovery. Still other improvements are architectural in nature, e.g., relating to evidence-based state machines, and blackboard systems. Yet other technologies concern use of linked data in portable devices—some of which exploit GPU capabilities. Still other technologies concern computational photography. A great variety of other features and arrangements are also detailed.

Optical code signal components are generated and then transformed into signal bearing art that conveys machine readable data. The components of an optical code are optimized to achieve improved signal robustness, reliability, capacity and/or visual quality. An optimization program can determine spatial density, dot distance, dot size and signal component priority to optimize robustness. An optical code generator transforms tiles of an optical code or image embedded with the optical code into signal-bearing art using stipple, Voronoi, Delaunay or other graphic drawing methods so as to retain prioritized components of the optical code. The optical code is merged into a host image, such as imagery, text and graphics of a package or label, or it may be printed by itself, e.g., on an otherwise blank label or carton. A great number of other features and arrangements are also detailed.