Abstract: A computerized method of routing customer interactions (call and chats) includes the following steps performed by a server computing device: creating a database with a document for every agent with a set of attributes identifying the types of customer interactions they service, receiving a set of call attributes associated with an incoming call; formulating a query of the call attributes against all agent profiles and returning a matching score for all available agents using Elastic Search; and routing the incoming call to a target agent with the highest score in the set of available agents, if there is at least one available agent; or a customer waiting queue, if there is no suitable agent achieving at least a minimum score.

Abstract: A computerized method of routing customer interactions (call and chats) includes the following steps performed by a server computing device: creating a database with a document for every agent with a set of attributes identifying the types of customer interactions they service, receiving a set of call attributes associated with an incoming call; formulating a query of the call attributes against all agent profiles and returning a matching score for all available agents using Elastic Search; and routing the incoming call to a target agent with the highest score in the set of available agents, if there is at least one available agent; or a customer waiting queue, if there is no suitable agent achieving at least a minimum score.

Abstract: A computerized method of routing calls includes the following steps performed by a server computing device: receiving a set of call attributes associated with an incoming call; identifying a document containing call routing instructions corresponding to the call attributes by querying a search index in electronic communication with the server computing device; identifying, based on the document, a set of suitable agents having a skill and a suitable proficiency in the skill by querying an agent skills database in electronic communication with the server computing device; identifying a set of available agents in the set of suitable agents by querying an agent status database in electronic communication with the server computing device; and routing the incoming call to a target agent in the set of available agents, if there is at least one available agent; or a customer waiting queue, if there is no suitable agent.

Abstract: A system and method determining a camera pose. The method comprises receiving a first image and a second image, the first and second images being associated with a camera pose and a height map for pixels in each corresponding image, and determining a mapping between the first image and the second image using the corresponding height maps, the camera pose and a mapping of the second image to an orthographic view. The method further comprises determining alignment data between the first image transformed using the determined mapping and the second image and determining a refined camera pose based on the determined alignment data and alignment data associated with at least one other camera pose.

Abstract: A computerized method of routing calls includes the following steps performed by a server computing device: receiving a set of call attributes associated with an incoming call; identifying a document containing call routing instructions corresponding to the call attributes by querying a search index in electronic communication with the server computing device; identifying, based on the document, a set of suitable agents having a skill and a suitable proficiency in the skill by querying an agent skills database in electronic communication with the server computing device; identifying a set of available agents in the set of suitable agents by querying an agent status database in electronic communication with the server computing device; and routing the incoming call to a target agent in the set of available agents, if there is at least one available agent; or a customer waiting queue, if there is no suitable agent.

Abstract: A system and method determining a camera pose. The method comprises receiving a first image and a second image, the first and second images being associated with a camera pose and a height map for pixels in each corresponding image, and determining a mapping between the first image and the second image using the corresponding height maps, the camera pose and a mapping of the second image to an orthographic view. The method further comprises determining alignment data between the first image transformed using the determined mapping and the second image and determining a refined camera pose based on the determined alignment data and alignment data associated with at least one other camera pose.

Abstract: A method of determining at least two motion values of an object moving axially in a scene. A first and second image of the object in the scene is captured with an image capture device. The object is axially displaced in the scene between the captured images with respect to a sensor plane of the image capture device. A variation in blur between the first and second captured images is determined. A scale change of the object between the first and second captured images is determined. Using the determined scale change and variation in blur, at least two motion values of the object in the scene are determined. The motion values identify the depths of the object in the first and second captured images and axial motion of the object in the scene.

Abstract: Methods, apparatuses, and computer readable storage media are provided for determining a depth measurement of a scene using an optical blur difference between two images of the scene. Each image is captured using an image capture device with different image capture device parameters. A corresponding image patch is identified from each of the captured images, motion blur being present in each of the image patches. A kernel of the motion blur in each of the image patches is determined. The kernel of the motion blur in at least one images patch is used to generate a difference convolution kernel. A selected first image patch is convolved with the generated difference convolution kernel to generate a modified image patch. A depth measurement of the scene is determined from an optical blur difference between the modified image patch and the remaining image patch.

Abstract: A method of determining at least two motion values of an object moving axially in a scene. A first and second image of the object in the scene is captured with an image capture device. The object is axially displaced in the scene between the captured images with respect to a sensor plane of the image capture device. A variation in blur between the first and second captured images is determined. A scale change of the object between the first and second captured images is determined. Using the determined scale change and variation in blur, at least two motion values of the object in the scene are determined. The motion values identify the depths of the object in the first and second captured images and axial motion of the object in the scene.

Abstract: Methods for determining a depth measurement of a scene which involve capturing at least two images of the scene with different camera parameters, and selecting corresponding image patches in each scene. A first approach calculates a plurality of complex responses for each image patch using a plurality of different quadrature filters, each complex response having a magnitude and a phase, assigns, for each quadrature filter, a weighting to the complex responses in the corresponding image patches, the weighting being determined by a relationship of the phases of the complex responses, and determines the depth measurement of the scene from a combination of the weighted complex responses.

Abstract: Methods, apparatuses, and computer readable storage media are provided for determining a depth measurement of a scene using an optical blur difference between two images of the scene. Each image is captured using an image capture device with different image capture device parameters. A corresponding image patch is identified from each of the captured images, motion blur being present in each of the image patches. A kernel of the motion blur in each of the image patches is determined. The kernel of the motion blur in at least one images patch is used to generate a difference convolution kernel. A selected first image patch is convolved with the generated difference convolution kernel to generate a modified image patch. A depth measurement of the scene is determined from an optical blur difference between the modified image patch and the remaining image patch.

Abstract: A method of modifying the blur in at least a part of an image of a scene captures at least two images of the scene with different camera parameters to produce a different amount of blur in each image. A corresponding patch in each of the captured images is selected each having an initial amount of blur is used to calculate a set of frequency domain pixel values from a function of transforms of the patches. Each of the pixel values in the set are raised to a predetermined power, forming an amplified set of frequency domain pixel values. The amplified set of frequency domain pixel values is combined with the pixels of the patch in one of the captured images to produce an output image patch with blur modified relative to the initial amount of blur in the image patch.

Abstract: A method of modifying the blur in at least a part of an image of a scene captures at least two images of the scene with different camera parameters to produce a different amount of blur in each image. A corresponding patch in each of the captured images is selected each having an initial amount of blur is used to calculate a set of frequency domain pixel values from a function of transforms of the patches. Each of the pixel values in the set are raised to a predetermined power, forming an amplified set of frequency domain pixel values. The amplified set of frequency domain pixel values is combined with the pixels of the patch in one of the captured images to produce an output image patch with blur modified relative to the initial amount of blur in the image patch.

Abstract: Methods for determining a depth measurement of a scene which involve capturing at least two images of the scene with different camera parameters, and selecting corresponding image patches in each scene. A first approach calculates a plurality of complex responses for each image patch using a plurality of different quadrature filters, each complex response having a magnitude and a phase, assigns, for each quadrature filter, a weighting to the complex responses in the corresponding image patches, the weighting being determined by a relationship of the phases of the complex responses, and determines the depth measurement of the scene from a combination of the weighted complex responses.