Simultaneous Multi-frame Subpixel Boundary Definition

using Toboggan-Based Intelligent Scissors

for Image and Movie Editing

Eric N. Mortensen

Brigham Young University
Intelligent Scissors is an interactive image segmentation tool that allows a user to select piece-wise globally optimal contour segments (based on an optimal path search in a graph) that correspond to a desired object boundary. This dissertation uses tobogganing to raise the granularity of the image primitive above the pixel level, producing a region-based basic processing unit that is object-centered rather than device-dependent. The resulting region-based elements form the basis for several contributions to the field of computer vision general and to Intelligent Scissors in particular. These contributions reduce the human time and effort needed for object selection with Intelligent Scissors while simultaneously increasing the accuracy of boundary definition.

The region-based image primitives resulting from tobogganing form the basis for a graph formulation that is many times smaller than the pixel-based graph used previously by Intelligent Scissors, thus providing faster, more interactively responsive optimal path computations. The object-centered atomic units also provide an efficient and consistent framework in which to compute a 4-parameter edge model, allowing subpixel boundary localization, noise-independent edge blur adjustment, and automatic alpha matte generation and color separation of boundary transition pixels. The increased size of the basic processing unit also facilitates an edge confidence measure that forms the basis for two new techniques called confidence threshold snapping and live-wire path extension, which further reduce the human burden involved with object boundary definition by automatically finding and following object boundaries. Finally, this dissertation presents a new paradigm for simultaneously interacting with multiple frames from a temporal image sequence by parallelizing both the user input and the interactive visual feedback, thus allowing a user to interact with a montage of image frames in order to define the boundary of a moving object while adhering to the same interactive style that has demonstrated to be effective for the single-image Intelligent Scissors.

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Section Size (gzipped Postscript) Size (PDF)
Intro (Title page, Abstract, Contents, etc.) 31,687 bytes 54,521 bytes
Chapter 1: Introduction 39,636 bytes 33,772 bytes
Chapter 2: Background and Related Work 989,045 bytes 407,966 bytes
Chapter 3: Toboggan-Based Intelligent Scissors 633,020 bytes 774,531 bytes
Chapter 4: Four-Parameter Edge Model 2,149,821 bytes 626,065 bytes
Chapter 5: Free-Point Splitting and Confidence Snapping 2,910,027 bytes 1,212,066 bytes
Chapter 6: Temporal Sequence Extensions 2,940,421 bytes 1,554,690 bytes
Chapter 7: Results and Discussion 4,343,958 bytes 2,052,664 bytes
Chapter 8: Conclusions and Future Directions 46,894 bytes 43,014 bytes
Bibliography 60,981 bytes 53,278 bytes

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