Abstract: A process mining system performs process mining using visual logs generated from video streams of worker devices. Specifically, for a given worker device, the process mining system obtains a series of images capturing a screen of a worker device while the worker device processes one or more tasks related to an operation process. The process mining system determines activity labels for a plurality of images. An activity label for an image may indicate an activity performed on the worker device when the image was captured. The activity label is determined by extracting information from pixels of the image and inferring the activity of the worker device from the extracted information. The process mining system generates event logs from the visual logs of worker devices and uses the event logs for process mining.

Abstract: A process mining system performs process mining using visual logs generated from video streams of worker devices. Specifically, for a given worker device, the process mining system obtains a series of images capturing a screen of a worker device while the worker device processes one or more tasks related to an operation process. The process mining system determines activity labels for a plurality of images. An activity label for an image may indicate an activity performed on the worker device when the image was captured. The activity label is determined by extracting information from pixels of the image and inferring the activity of the worker device from the extracted information. The process mining system generates event logs from the visual logs of worker devices and uses the event logs for process mining.

Abstract: A process mining system performs process mining using visual logs generated from video streams of worker devices. Specifically, for a given worker device, the process mining system obtains a series of images capturing a screen of a worker device while the worker device processes one or more tasks related to an operation process. The process mining system determines activity labels for a plurality of images. An activity label for an image may indicate an activity performed on the worker device when the image was captured. The activity label is determined by extracting information from pixels of the image and inferring the activity of the worker device from the extracted information. The process mining system generates event logs from the visual logs of worker devices and uses the event logs for process mining.

Abstract: A process mining system performs process mining using visual logs generated from video streams of worker devices. Specifically, for a given worker device, the process mining system obtains a series of images capturing a screen of a worker device while the worker device processes one or more tasks related to an operation process. The process mining system determines activity labels for a plurality of images. An activity label for an image may indicate an activity performed on the worker device when the image was captured. The activity label is determined by extracting information from pixels of the image and inferring the activity of the worker device from the extracted information. The process mining system generates event logs from the visual logs of worker devices and uses the event logs for process mining.

Abstract: The present invention provides a method and apparatus for selectively enhancing regions in an image. In one embodiment, a digital image is read from an image source and is converted into a desired image model. One or more regions in the image having intensity values of pixels falling outside a pre-determined optimal intensity range are determined. The one or more regions in the image are then enhanced using a modeled light source of an optimal intensity such that the intensity value of pixels corresponding to the one or more regions in the image fall within the pre-determined optimal intensity range.

Abstract: The present invention provides a method and apparatus for selectively enhancing regions in an image. In one embodiment, a digital image is read from an image source and is converted into a desired image model. One or more regions in the image having intensity values of pixels falling outside a pre-determined optimal intensity range are determined. The one or more regions in the image are then enhanced using a modeled light source of an optimal intensity such that the intensity value of pixels corresponding to the one or more regions in the image fall within the pre-determined optimal intensity range.