Abstract: Various aspects of the present disclosure generally relate to a sensor module. In some aspects, a sensor module may include a collar configured to be attached to a camera module for a user device. The collar may include a first opening that is configured to align with an aperture of a camera of the camera module, and a second opening. The sensor module may include a sensor embedded in the collar. The sensor may be aligned with the second opening of the collar. Numerous other aspects are provided.

Abstract: A connected oven, including a set of in-cavity sensors and a processor configured to automatically identify foodstuff within the cooking cavity, based on the sensor measurements; and automatically operate the heating element based on the foodstuff identity.

Abstract: Methods for aligning a digital 3D model of teeth represented by a 3D mesh to a desired orientation within a 3D coordinate system. The method includes receiving the 3D mesh in random alignment and changing an orientation of the 3D mesh to align the digital 3D model of teeth with a desired axis in the 3D coordinate system. The methods can also detect a gum line in the digital 3D model to remove the gingiva from the model.

Abstract: A connected oven, including a set of in-cavity sensors and a processor configured to automatically identify foodstuff within the cooking cavity, based on the sensor measurements; and automatically operate the heating element based on the foodstuff identity.

Abstract: A connected oven, including a set of in-cavity sensors and a processor configured to automatically identify foodstuff within the cooking cavity, based on the sensor measurements; and automatically operate the heating element based on the foodstuff identity.

Abstract: Certain aspects of the present disclosure relate to a system. In some aspects, the system may include an emitter configured to emit a light. The system may include a light guide configured to direct the light toward a pupil of an eye. The light guide may include a directing portion configured to propagate the light. The light guide may include a turning portion configured to receive light from the directing portion and direct the light toward the pupil of the eye and configured to receive reflected light directed from the pupil of the eye and direct the reflected light toward the directing portion. The system may include a receiver configured to receive the reflected light from the light guide. The system may include a processor configured to determine a gaze direction of the pupil of the eye based at least in part on the reflected light received by the receiver.

Abstract: Cameras with large field-of-view lenses can cause significant geometric distortions of the images acquired. Training for object detection normally takes place on undistorted images. Thus, in order to detect objects of interest within the acquired images, an undistortion procedure is applied on the acquired images and an object detection is then performed on the undistorted images. Unfortunately, such undistortion procedure is too computationally expensive to be run on some edge devices. To remove the need to perform the undistortion procedure, it is proposed to train for object detection directly from distorted acquired images.

Abstract: A connected oven, including a set of in-cavity sensors and a processor configured to automatically identify foodstuff within the cooking cavity, based on the sensor measurements; and automatically operate the heating element based on the foodstuff identity.

Abstract: A connected oven, including a set of in-cavity sensors and a processor configured to automatically identify foodstuff within the cooking cavity, based on the sensor measurements; and automatically operate the heating element based on the foodstuff identity.

Abstract: A connected oven, including a set of in-cavity sensors and a processor configured to automatically identify foodstuff within the cooking cavity, based on the sensor measurements; and automatically operate the heating element based on the foodstuff identity.

Abstract: Systems and methods for authenticating material samples are provided. Characteristic features are measured for a batch of material samples that comprise substantially the same composition and are produced by substantially the same process. The measured characteristic features have respective variability that is analyzed to extract statistical parameters. In some cases, reference ranges are determined based on the extracted statistical parameters for the batch of material samples. The corresponding statistical parameters of a test material sample are compared to the reference ranges to verify whether the test material sample is authentic.

Abstract: Techniques are presented for detecting a visual marker. A first image containing the visual marker may be captured at a first time under a first lighting condition. A first image-based detection for the visual marker may be performed based on the first image, using a first detector, to produce a first set of results. A second image containing the visual marker may be captured at a second time under a second lighting condition different from the first lighting condition. Based on the first set of results, a second image-based detection for the visual marker may be performed based on the second image, using a second detector different from the first detector, to produce a second set of results.

Abstract: Methods for estimating and predicting tooth wear based upon a single 3D digital model of teeth. The 3D digital model is segmented to identify individual teeth within the model. A digital model of a tooth is selected from the segmented model, and its original shape is predicted. The digital model is compared with the predicted original shape to estimate wear areas. A mapping function based upon values relating to tooth wear can also be applied to the selected digital model to predict wear of the tooth.

Abstract: A method for detecting tooth wear using digital 3D models of teeth taken at different times. The digital 3D models of teeth are segmented to identify individual teeth within the digital 3D model. The segmentation includes performing a first segmentation method that over segments at least some of the teeth within the model and a second segmentation method that classifies points within the model as being either on an interior of a tooth or on a boundary between teeth. The results of the first and second segmentation methods are combined to generate segmented digital 3D models. The segmented digital 3D models of teeth are compared to detect tooth wear by determining differences between the segmented models, where the differences relate to the same tooth to detect wear on the tooth over time.

Abstract: A connected oven, including a set of in-cavity sensors and a processor configured to automatically identify foodstuff within the cooking cavity, based on the sensor measurements; and automatically operate the heating element based on the foodstuff identity.

Abstract: Systems and methods for generating random bits by using physical variations present in material samples are provided. Initial random bit streams are derived from measured material properties for the material samples. In some cases, secondary random bit streams are generated by applying a randomness extraction algorithm to the derived initial random bit streams.

Abstract: Techniques for creating and manipulating software notes representative of physical notes are described. A computing device includes a processor, an image collection module executable by the processor and configured to receive an input image of an environment having a plurality of overlapping physical notes, and an image processing engine executable by the processor and configured to process the input image with the computing device to identify the plurality of overlapping physical notes in the input image. The image processing engine determines a boundary of each note in the plurality of overlapping physical notes in the input image, and generates a plurality of digital notes corresponding to the determined boundary of each of the overlapping physical notes identified in the input image.

Abstract: Methods for aligning a digital 3D model of teeth represented by a 3D mesh to a desired orientation within a 3D coordinate system. The method includes receiving the 3D mesh in random alignment and changing an orientation of the 3D mesh to align the digital 3D model of teeth with a desired axis in the 3D coordinate system. The methods can also detect a gum line in the digital 3D model to remove the gingiva from the model.

Abstract: Reconstructed surface meshes can be generated based on a plurality of received surface meshes. Each surface mesh can include vertices and faces representing an object. The received surface meshes can be assigned to one of a plurality of groups, and a region of interest of each surface mesh within each group can be aligned. The reconstructed surface meshes can be generated based on the aligned regions of interest for each group.

Abstract: Methods for aligning a digital 3D model of teeth represented by a 3D mesh to a desired orientation within a 3D coordinate system. The method includes receiving the 3D mesh in random alignment and changing an orientation of the 3D mesh to align the digital 3D model of teeth with a desired axis in the 3D coordinate system. The methods can also detect a gum line in the digital 3D model to remove the gingiva from the model.