Abstract: A 3-dimensional tracking and navigation simulator system for image guided neuro-endoscopy, said system comprising: a fiducial based physical model of an anatomic region associated with neuro-endoscopy, wherein the physical model is mapped with CT/MRI slices of the anatomy; a virtual model of the anatomic region associated with neuro-endoscopy; at least one surgical instrument operable to perform neuro-endoscopy, said at least one surgical instrument is associated with a 3-D tracking component; a camera unit for tracking a location of the at least one surgical instrument with the 3-D tracking component, relative to a reference unit of the physical model; one or more displays for displaying the location of the at least one surgical instrument in the CT/MRI slices and endoscopic output, a computer work-station operably coupled to the physical model, and the camera unit, said work-station comprising: a localization and tracking module having configured to track the tasks performed by a user with the at least one

Abstract: A system and method for generating an optimized image with scribble-based interactive image segmentation model using a machine learning are provided. The method includes, (i) segmenting, using a machine learning model, an image to classify into classes each class is represented with a label, (ii) displaying the classified image which specifies the classes on the classified image with outlines, (iii) enabling a user to scribble on the classified image to annotate the classes if an area is not classified, (iv) assigning a color mask for each scribbled area, (v) computing, using the machine learning model, a loss function for a location of pixels based on color mask, (vi) modifying pre-defined weights for each scribbled area to match the annotated image and a determined class on the classified image, and (vii) generating the optimized image if the annotated image is matched with the determined class on the classified image.

Abstract: A system and method generating an optimized medical image using a machine learning model are provided. The method includes (i) receiving one or more medical images, (ii) segmenting to generate a transformed medical image for detecting a plurality of target elements, (iii) displaying the transformed medical image, (iv) receiving markings and scribblings associated with scribble locations from a user, (v) identifying errors associated with an outline of a target element, (vi) computing a loss function for a location of pixels where the target element is located on the transformed medical image, (vii) modifying the pre-defined weights (w) to match the segmentation output and the determined target element, (viii) determining whether the segmentation output is matched with the target element and (ix) generating the optimized medical image if the segmentation output is matched with the determined target element.

Abstract: A method for generating a derained image using a self-supervised learning model is provided. The method includes (i) processing an input image received from a user device; (ii) classifying pixels of the input image as rainy or non-rainy pixels by assigning a first value to the rainy pixels and a second value to the non-rainy pixels; (iii) generating a masked area in the input image by masking out the rainy pixels from the input image based on the rainy pixels; (iv) generating an inpainted image by filling the masked area using an image inpainting method; and (v) generating an optimized image by deraining the inpainted image and remove image artifacts and blurriness caused by the image inpainting method. The optimized image enables an improved semantic segmentation of the input image and object detection.

Abstract: A method for detecting object in an image in a target environment that is adapted to a source environment using a machine learning model is provided.

Abstract: A system and method for generating an optimized image with scribble-based interactive image segmentation model using a machine learning are provided. The method includes, (i) segmenting, using a machine learning model, an image to classify into classes each class is represented with a label, (ii) displaying the classified image which specifies the classes on the classified image with outlines, (iii) enabling a user to scribble on the classified image to annotate the classes if an area is not classified, (iv) assigning a color mask for each scribbled area, (v) computing, using the machine learning model, a loss function for a location of pixels based on color mask, (vi) modifying pre-defined weights for each scribbled area to match the annotated image and a determined class on the classified image, and (vii) generating the optimized image if the annotated image is matched with the determined class on the classified image.

Abstract: A system and method generating an optimized medical image using a machine learning model are provided. The method includes (i) receiving one or more medical images, (ii) segmenting to generate a transformed medical image for detecting a plurality of target elements, (iii) displaying the transformed medical image, (iv) receiving markings and scribblings associated with scribble locations from a user, (v) identifying errors associated with an outline of a target element, (vi) computing a loss function for a location of pixels where the target element is located on the transformed medical image, (vii) modifying the pre-defined weights (w) to match the segmentation output and the determined target element, (viii) determining whether the segmentation output is matched with the target element and (ix) generating the optimized medical image if the segmentation output is matched with the determined target element.

Abstract: A method and a system for generating adaptive fast forward of egocentric videos are provided here. The method may include the following steps: obtaining a video footage containing a sequence of image frames captured by a non-stationary capturing device; estimating a moving direction of the non-stationary capturing device for a plurality of frames in the sequence of image frames; and generating a shortened video footage having fewer frames than said video footage, by sampling the sequence of image frames, wherein the sampling is carried out by selecting specific image frames and that minimize an overall cost associated with a deviation from a specific direction related to the moving direction, calculated for each of said plurality of image frames.

Abstract: A method and a system for generating adaptive fast forward of egocentric videos are provided here. The method may include the following steps: obtaining a video footage containing a sequence of image frames captured by a non-stationary capturing device; estimating a moving direction of the non-stationary capturing device for a plurality of frames in the sequence of image frames; and generating a shortened video footage having fewer frames than said video footage, by sampling the sequence of image frames, wherein the sampling is carried out by selecting specific image frames and that minimize an overall cost associated with a deviation from a specific direction related to the moving direction, calculated for each of said plurality of image frames.

Abstract: A method and a system for generating adaptive fast forward of egocentric videos are provided here. The method may include the following steps: obtaining a video footage containing a sequence of image frames captured by a non-stationary capturing device; estimating a moving direction of the non-stationary capturing device for a plurality of frames in the sequence of image frames; and generating a shortened video footage having fewer frames than said video footage, by sampling the sequence of image frames, wherein the sampling is carried out by selecting specific image frames and that minimize an overall cost associated with a deviation from a specific direction related to the moving direction, calculated for each of said plurality of image frames.

Abstract: Authentication method that provides: to make an authentication device, randomly attaching a plurality of reflecting particles, such as glitter, on a support; a first step of acquiring, with an optical acquisition device, at least two first images of the authentication device, the two first images each being acquired according to different lighting conditions; a first step of encoding each of the two first images in order to determine at least a first identifying indicator to be attributed to the authentication device.

Abstract: A method and a system for generating adaptive fast forward of egocentric videos are provided here. The method may include the following steps: obtaining a video footage containing a sequence of image frames captured by a non-stationary capturing device; estimating a moving direction of the non-stationary capturing device for a plurality of frames in the sequence of image frames; and generating a shortened video footage having fewer frames than said video footage, by sampling the sequence of image frames, wherein the sampling is carried out by selecting specific image frames and that minimize an overall cost associated with a deviation from a specific direction related to the moving direction, calculated for each of said plurality of image frames.

Abstract: A method and a system for generating adaptive fast forward of egocentric videos are provided here. The method may include the following steps: obtaining a video footage containing a sequence of image frames captured by a non-stationary capturing device; estimating a moving direction of the non-stationary capturing device for a plurality of frames in the sequence of image frames; and generating a shortened video footage having fewer frames than said video footage, by sampling the sequence of image frames, wherein the sampling is carried out by selecting specific image frames and that minimize an overall cost associated with a deviation from a specific direction related to the moving direction, calculated for each of said plurality of image frames.

Abstract: A system and method for generating a mosaic image from respective regions in a plurality of individual images, at least one of the regions being distorted and having a left and/or right edge that is tilted relative to a direction of view of the respective image. The distorted regions are rectified so as to form a respective rectified rectangular region and at least some of the rectified rectangular regions are mosaiced to form the mosaic image.

Abstract: A system is described for generating a rectified mosaic image from a plurality of individual images, the system comprising a quadrangular region defining module, a warping module and a mosaicing module. The quadrangular region defining module is configured to define in one individual image a quadrangular region in relation to two points on a vertical anchor in the one individual image and mappings of two points on a vertical anchor in at least one other individual image into the one individual image. The warping module is configured to warp the quadrangular region to a rectangular region. The mosaicing module configured to mosaic the quadrangular region to the mosaic image. The system further generates a mosaic from a plurality of panoramic images, the system comprising a motion determining module, a normalizing module, a strip selection module, and a mosaicing module. The motion determining module is configured to determine image motion between two panoramic images.