Abstract: A mechanism is described for facilitating smart capturing of whiteboard contents according to one embodiment. A method of embodiments, as described herein, includes capturing, by one or more cameras of a computing device, one or more images of one or more boards, and identifying a target board of the one or more boards using one or more indicators associated with the target board, where identifying the target board includes extracting a region encompassing the target board. The method may further include estimating scene geometry based on the region, and generating a rectified image of the target board based on the scene geometry.

Abstract: An automated object tracking system for tracking a colored object through a series of frames of data. The system has a first image source device to provide a data array of pixels of a digital image. A second image source device provides a binary image of the data array. The system utilizes an analysis system to create a first histogram for columns of the binary image and a second histogram for rows of the binary image. Each histogram is thresholded, and after being thresholding, is utilized to estimate the center of a tracked object in the binary image.

Abstract: A method and system of transforming a source code file to obtain a reduced size source code file. In one embodiment, a source code file is translated to obtain a translation error list. The source code file is transformed to obtain a reduced size source code file, which is a test case file that is equivalent to the source code file. In one embodiment, a source code file is translated to obtain a translation error list and a reduced size source code file is automatically translated to obtain a reduced size source code file translation error list. The error lists are compared in order to determine whether the reduced size source code file is an equivalent test case for the source code file.

Abstract: An automated calibration system for tracking a colored object through a series of frames of data. The calibration system has a first processing device that executes a program, the program displaying at least one image frame from an image input device. An image selection device is utilized to select an object in one of the image frames. An image source device provides a hue-saturation-value (HSV) data array of pixels in the object. An HSV thresholding device thresholds the HSV data array of the pixels in the object. The system also has a second processing device that analyzes the HSV data array. The second processing device determines characteristics of the pixels in the at least one image frame that are to be associated with the object based on a probability.

Abstract: An automated object tracking system for tracking a colored object through a series of frames of data. The system has a first image source device to provide a data array of pixels of a digital image. A second image source device provides a binary image of the data array. The system utilizes an analysis system to create a first histogram for columns of the binary image and a second histogram for rows of the binary image. Each histogram is thresholded, and after being thresholding, is utilized to estimate the center of a tracked object in the binary image.