Abstract: Various embodiments are disclosed for simultaneous object localization and attribute classification using multitask deep neural networks. In an embodiment, a method comprises: obtaining, by a processing circuit, an image from an image capture device in an environment, the image including a target object in the environment; generating, by the processing circuit, predictions from the image for the target object using a multitask deep neural network, the multitask deep neural network including a network trunk and side branches, the network trunk configured for multi-scale feature extraction guided by supervision information provided by the side branches during training of the multitask deep neural network, the side branches configured as learning task-specific classifiers; and using, by the processing circuit, the predictions to localize the target object in the environment and to classify the target object and at least one attribute of the target object.

Abstract: Various embodiments are disclosed for detecting, tracking and counting objects of interest in video frames using fusion of image and depth modalities. In an embodiment, a method comprises: obtaining multiple frames of stereo image pairs from an image capturing device; rectifying each frame of the stereo image pairs; computing a stereo disparity for each frame of the stereo image pairs; determining a first set of object detections in each frame using the computed stereo disparity; determining a second set of object detections in each left or right frame of the stereo image pair using one or more machine learning models; fusing the first and second sets of object detections; and creating tracks based on the fused object detections.

Abstract: Various embodiments are disclosed for detecting, tracking and counting objects of interest in video. In an embodiment, a method of detecting and tracking objects of interest comprises: obtaining, by a computing device, multiple frames of images from an image capturing device; detecting, by the computing device, objects of interest in each frame; accumulating, by the computing device, multiple frames of object detections; creating, by the computing device, object tracks based on a batch of object detections over multiple frames; and associating, by the computing device, the object tracks over consecutive batches.

Abstract: Various embodiments are disclosed for detecting, tracking and counting objects of interest in video. In an embodiment, a method of detecting and tracking objects of interest comprises: obtaining, by a computing device, multiple frames of images from an image capturing device; detecting, by the computing device, objects of interest in each frame; accumulating, by the computing device, multiple frames of object detections; creating, by the computing device, object tracks based on a batch of object detections over multiple frames; and associating, by the computing device, the object tracks over consecutive batches.

Abstract: Various embodiments are disclosed for detecting, tracking and counting objects of interest in video. In an embodiment, a method of detecting and tracking objects of interest comprises: obtaining, by a computing device, multiple frames of images from an image capturing device; detecting, by the computing device, objects of interest in each frame; accumulating, by the computing device, multiple frames of object detections; creating, by the computing device, object tracks based on a batch of object detections over multiple frames; and associating, by the computing device, the object tracks over consecutive batches.

Abstract: Various embodiments are disclosed for simultaneous object localization and attribute classification using multitask deep neural networks. In an embodiment, a method comprises: obtaining, by a processing circuit, an image from an image capture device in an environment, the image including a target object in the environment; generating, by the processing circuit, predictions from the image for the target object using a multitask deep neural network, the multitask deep neural network including a network trunk and side branches, the network trunk configured for multi-scale feature extraction guided by supervision information provided by the side branches during training of the multitask deep neural network, the side branches configured as learning task-specific classifiers; and using, by the processing circuit, the predictions to localize the target object in the environment and to classify the target object and at least one attribute of the target object.

Abstract: Various embodiments are disclosed for detecting, tracking and counting objects of interest in video frames using fusion of image and depth modalities. In an embodiment, a method comprises: obtaining multiple frames of stereo image pairs from an image capturing device; rectifying each frame of the stereo image pairs; computing a stereo disparity for each frame of the stereo image pairs; determining a first set of object detections in each frame using the computed stereo disparity; determining a second set of object detections in each left or right frame of the stereo image pair using one or more machine learning models; fusing the first and second sets of object detections; and creating tracks based on the fused object detections.

Abstract: Various embodiments are disclosed for detecting, tracking and counting objects of interest in video. In an embodiment, a method of detecting and tracking objects of interest comprises: obtaining, by a computing device, multiple frames of images from an image capturing device; detecting, by the computing device, objects of interest in each frame; accumulating, by the computing device, multiple frames of object detections; creating, by the computing device, object tracks based on a batch of object detections over multiple frames; and associating, by the computing device, the object tracks over consecutive batches.

Abstract: A system, method and non-transitory, computer-readable storage medium are disclosed for point-of-sale (POS) fraud detection using, POS transaction data, video data and statistical evaluations of employee behavior. In an embodiment, the POS transaction data, video data and statistical evaluations are used to examine patterns of individual employees of an organization versus metrics across all employees of the organization to identify employees that are most likely to perform a fraudulent transaction.

Abstract: A wireless analytics system and method are disclosed that take shoppers through an initial registration process, after which they can access the Internet quickly and easily every time they visit any of the retailer's stores. During future visits to any of the retailer's store locations the shopper's device is automatically granted network access as soon as it is within wireless range. Once on the network, a shopper can access websites, social networks, and shopping resources from across the mobile web. The system collects information about these access events, including the location and timestamp of each access event. The retailer may be notified when a shopper enters their store. This information may automate the check-in process for processes within the retail store or within a mobile application.

Abstract: Various embodiments are disclosed for detecting, tracking and counting objects of interest in video. In an embodiment, a method of detecting and tracking objects of interest comprises: obtaining, by a computing device, multiple frames of images from an image capturing device; detecting, by the computing device, objects of interest in each frame; accumulating, by the computing device, multiple frames of object detections; creating, by the computing device, object tracks based on a batch of object detections over multiple frames; and associating, by the computing device, the object tracks over consecutive batches.

Abstract: In some implementations, video camera networks can be used to track people or objects and determine their locations. In some implementations, location accuracy better than one meter can be achieved using video cameras. According to some implementations, Wi-Fi localization and video localization systems can be fused together to perform calibration. In some implementations, by using the video network to continuously update the Wi-Fi localization calibration database, Wi-Fi location accuracy can be improved.

Abstract: According to some implementations, an estimate of a target's location can be calculated by correlating Wi-Fi and video location measurements. This spatio-temporal correlation combines the Wi-Fi and video measurements to determine an identity and location of an object. The accuracy of the video localization and the identity from the Wi-Fi network provide an accurate location of the Wi-Fi identified object.

Abstract: According to some implementations, an estimate of a target's location can be calculated by correlating Wi-Fi and video location measurements. This spatio-temporal correlation combines the Wi-Fi and video measurements to determine an identity and location of an object. The accuracy of the video localization and the identity from the Wi-Fi network provide an accurate location of the Wi-Fi identified object.

Abstract: A wireless analytics system and method are disclosed that take shoppers through an initial registration process, after which they can access the Internet quickly and easily every time they visit any of the retailer's stores. During future visits to any of the retailer's store locations the shopper's device is automatically granted network access as soon as it is within wireless range. Once on the network, a shopper can access websites, social networks, and shopping resources from across the mobile web. The system collects information about these access events, including the location and timestamp of each access event. The retailer may be notified when a shopper enters their store. This information may automate the check-in process for processes within the retail store or within a mobile application.

Abstract: According to some implementations, an estimate of a target's location can be calculated by correlating Wi-Fi and video location measurements. This spatio-temporal correlation combines the Wi-Fi and video measurements to determine an identity and location of an object. The accuracy of the video localization and the identity from the Wi-Fi network provide an accurate location of the Wi-Fi identified object.

Abstract: According to some implementations, an estimate of a target's location can be calculated by correlating Wi-Fi and video location measurements. This spatio-temporal correlation combines the Wi-Fi and video measurements to determine an identity and location of an object. The accuracy of the video localization and the identity from the Wi-Fi network provide an accurate location of the Wi-Fi identified object.

Abstract: In some implementations, video camera networks can be used to track people or objects and determine their locations. In some implementations, location accuracy better than one meter can be achieved using video cameras. According to some implementations, Wi-Fi localization and video localization systems can be fused together to perform calibration. In some implementations, by using the video network to continuously update the Wi-Fi localization calibration database, Wi-Fi location accuracy can be improved.

Abstract: A content delivery system and method are provided in which different types of content may be delivered to different information appliances having different protocols and different browser specifications. The system permits internet content providers to create a single piece of content that is re-formatted automatically for the different information appliances.