Abstract: Disclosed are methods and systems of controlling the placement of micro-objects on the surface of a micro-assembler. Control patterns may be used to cause electrodes of the micro-assembler to generate dielectrophoretic (DEP) and electrophoretic (EP) forces which may be used to manipulate, move, position, or orient one or more micro-objects on the surface of the micro-assembler. The control patterns may be part of a library of control patterns.

Abstract: Disclosed are methods and systems of controlling the placement of micro-objects on the surface of a micro-assembler. Control patterns may be used to cause electrodes of the micro-assembler to generate dielectrophoretic (DEP) and electrophoretic (EP) forces which may be used to manipulate, move, position, or orient one or more micro-objects on the surface of the micro-assembler. The control patterns may be part of a library of control patterns.

Abstract: One embodiment can provide a system for detecting a difference between a physical object and a reference model corresponding to the physical object. During operation, the system obtains a real-world image of the physical object and generates an augmented reality (AR) image by projecting a three-dimensional overlay generated from the reference model onto the physical object in the real-world image. While generating the AR image, the system aligns a pose of the reference model to a pose of the physical object. The system can detect the difference between the physical object and the reference model based on the generated AR image and the real-world image.

Abstract: One embodiment provides a system that facilitates efficient collection of training data. During operation, the system obtains, by a recording device, a first image of a physical object in a scene which is associated with a three-dimensional (3D) world coordinate frame. The system marks, on the first image, a plurality of vertices associated with the physical object, wherein a vertex has 3D coordinates based on the 3D world coordinate frame. The system obtains a plurality of second images of the physical object in the scene while changing one or more characteristics of the scene. The system projects the marked vertices on to a respective second image to indicate a two-dimensional (2D) bounding area associated with the physical object.

Abstract: A three-dimensional geometry of an object is stored, and a representation of the object that can facilitate identification of the object via a camera is also stored. An image of the object is obtained via a scene in the camera. The presence of the object is detected from the image via the stored representation of the object. The three-dimensional geometry to the object is mapped within the scene based on the detection. A virtual object is attached to a point that is at a fixed orientation relative to the three-dimensional geometry based on the mapping. The virtual object is rendered on an augmented reality display as being located at the point and at the fixed orientation regardless of a change in location of the augmented reality display relative to the object.

Abstract: Disclosed are methods and systems of controlling the placement of micro-objects on the surface of a micro-assembler. Control patterns may be used to cause electrodes of the micro-assembler to generate dielectrophoretic (DEP) and electrophoretic (EP) forces which may be used to manipulate, move, position, or orient one or more micro-objects on the surface of the micro-assembler. The control patterns may be part of a library of control patterns.

Abstract: Disclosed are methods and systems of controlling the placement of micro-objects on the surface of a micro-assembler. Control patterns may be used to cause phototransistors or electrodes of the micro-assembler to generate dielectrophoretic (DEP) and electrophoretic (EP) forces which may be used to manipulate, move, position, or orient one or more micro-objects on the surface of the micro-assembler. A set of micro-object may be analyzed. Geometric properties of the set of micro-objects may be identified. The set of micro-objects may be divided into multiple sub-sets of micro-objects based on the one or more geometric properties and one or more control patterns.

Abstract: Disclosed are methods and systems of controlling the placement of micro-objects on the surface of a micro-assembler. Control patterns may be used to cause phototransistors or electrodes of the micro-assembler to generate dielectrophoretic (DEP) and electrophoretic (EP) forces which may be used to manipulate, move, position, or orient one or more micro-objects on the surface of the micro-assembler. A set of micro-object may be analyzed. Geometric properties of the set of micro-objects may be identified. The set of micro-objects may be divided into multiple sub-sets of micro-objects based on the one or more geometric properties and one or more control patterns.

Abstract: One embodiment provides a system that facilitates efficient collection of training data. During operation, the system obtains, by a recording device, a first image of a physical object in a scene which is associated with a three-dimensional (3D) world coordinate frame. The system marks, on the first image, a plurality of vertices associated with the physical object, wherein a vertex has 3D coordinates based on the 3D world coordinate frame. The system obtains a plurality of second images of the physical object in the scene while changing one or more characteristics of the scene. The system projects the marked vertices on to a respective second image to indicate a two-dimensional (2D) bounding area associated with the physical object.

Abstract: A method of processing image data includes: capturing an image with a camera; selecting one or more regions of interest within the captured image; analyzing the selected regions of interest to detect objects appearing therein, such that each detected object has a bounding therearound defining an image crop; for each image crop, iteratively compressing image data corresponding thereto, while varying one or more parameters with each successive iteration, until the compressed image data meets a target size; and transmitting the compressed image data meeting the target size over a wireless telecommunications link having a data rate limit imposed for such transmitting.

Abstract: A three-dimensional geometry of an object is stored, and a representation of the object that can facilitate identification of the object via a camera is also stored. An image of the object is obtained via a scene in the camera. The presence of the object is detected from the image via the stored representation of the object. The three-dimensional geometry to the object is mapped within the scene based on the detection. A virtual object is attached to a point that is at a fixed orientation relative to the three-dimensional geometry based on the mapping. The virtual object is rendered on an augmented reality display as being located at the point and at the fixed orientation regardless of a change in location of the augmented reality display relative to the object.

Abstract: One embodiment can provide a system for detecting a difference between a physical object and a reference model corresponding to the physical object. During operation, the system obtains a real-world image of the physical object and generates an augmented reality (AR) image by projecting a three-dimensional overlay generated from the reference model onto the physical object in the real-world image. While generating the AR image, the system aligns a pose of the reference model to a pose of the physical object. The system can detect the difference between the physical object and the reference model based on the generated AR image and the real-world image.

Abstract: A method includes receiving a user object specified by a user. A similarity score is computed using a similarity function between the user object and one or more candidate objects in a database based on respective feature vectors. A first subset of the one or more candidate objects is presented to the user based on the respective computed similarity scores. First feedback is received from the user about the first subset of candidate objects. The similarity function is adjusted based on the received first feedback.

Abstract: One embodiment can include a system for providing an image-capturing recommendation. During operation the system receives, from a mobile computing device, one or more images. The one or more images are captured by one or more cameras associated with the mobile computing device. The system analyzes the received images to obtain image-capturing conditions for capturing images of a target within a physical space; determines, based on the obtained image-capturing conditions and a predetermined image-quality requirement, one or more image-capturing settings; and recommends the determined one or more image-capturing settings to a user.

Abstract: Embodiments described herein provide a system for facilitating efficient dataset management. During operation, the system obtains a first dataset comprising a plurality of elements. The system then determines a set of categories for a respective element of the plurality of elements by applying a plurality of AI models to the first dataset. A respective category can correspond to an AI model. Subsequently, the system selects a set of sample elements associated with a respective category of a respective AI model and determines a second dataset based on the selected sample elements.

Abstract: A method for predicting the realism of an object within an image includes generating a training image set for a predetermined object type. The training image set comprises one or more training images at least partially generated using a computer. A pixel level training spatial realism map is generated for each training image of the one or more training images. Each training spatial realism map configured to represent a perceptual realism of the corresponding training image. A predictor is trained using the training image set and the corresponding training spatial realism maps. An image of the predetermined object is received. A spatial realism map of the received image is produced using the trained predictor.

Abstract: An apparatus comprises an input interface configured to receive a first 3D point cloud associated with a physical object prior to articulation of an articulatable part, and a second 3D point cloud after articulation of the articulatable part. A processor is operably coupled to the input interface, an output interface, and memory. Program code, when executed by the processor, causes the processor to align the first and second point clouds, find nearest neighbors of points in the first point cloud to points in the second point cloud, eliminate the nearest neighbors of points in the second point cloud such that remaining points in the second point cloud comprise points associated with the articulatable part and points associated with noise, generate an output comprising at least the remaining points of the second point cloud associated with the articulatable part without the noise points, and communicate the output to the output interface.

Abstract: When monitoring a workspace to determine whether scheduled tasks or chores are completed according to a predetermined schedule, a video monitoring system monitors a region of interest (ROI) to identify employee-generated signals representing completion of a scheduled task. An employee makes a mark or gesture in the ROI monitored by the video monitoring system and the system analyzes pixels in each captured frame of the ROI to identify an employee signal, map the signal to a corresponding scheduled task, update the task as having been completed upon receipt of the employee signal, and alert a manager of the facility as to whether the task has been completed or not.

Abstract: An apparatus comprises an input interface configured to receive a first 3D point cloud associated with a physical object prior to articulation of an articulatable part, and a second 3D point cloud after articulation of the articulatable part. A processor is operably coupled to the input interface, an output interface, and memory. Program code, when executed by the processor, causes the processor to align the first and second point clouds, find nearest neighbors of points in the first point cloud to points in the second point cloud, eliminate the nearest neighbors of points in the second point cloud such that remaining points in the second point cloud comprise points associated with the articulatable part and points associated with noise, generate an output comprising at least the remaining points of the second point cloud associated with the articulatable part without the noise points, and communicate the output to the output interface.

Abstract: One embodiment provides a system that facilitates efficient collection of training data for training an image-detection artificial intelligence (AI) engine. During operation, the system obtains a three-dimensional (3D) model of a physical object placed in a scene, generates a virtual object corresponding to the physical object based on the 3D model, and substantially superimposes, in a view of an augmented reality (AR) camera, the virtual object over the physical object. The system can further configure the AR camera to capture a physical image comprising the physical object in the scene and a corresponding AR image comprising the virtual object superimposed over the physical object, and create an annotation for the physical image based on the AR image.