By Krishna Nathan (auth.), Roland Chin, Ting-Chuen Pong (eds.)
These volumes represent the refereed court cases of the 3rd Asian convention on computing device imaginative and prescient, ACCV'98, held in Hong Kong, China, in January 1998. The volumes current jointly a complete of fifty eight revised complete papers and 112 revised posters chosen from over three hundred submissions. The papers are equipped in topical sections on biometry, physics-based imaginative and prescient, colour imaginative and prescient, robotic imaginative and prescient and navigation, OCR and functions, low-level processing, energetic imaginative and prescient, face and hand posture attractiveness, segmentation and grouping, desktop imaginative and prescient and digital truth, movement research, and item popularity and modeling.
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Extra info for Computer Vision — ACCV'98: Third Asian Conference on Computer Vision Hong Kong, China, January 8–10, 1998 Proceedings, Volume I
17. White λ -moves 3 Definition 4. A quasi-liberty corresponding to a λ -tree is a liberty that is not coincin dent with a shadow stone corresponding to the λ -tree. (The number of quasi-liberties will always be ≤ the number of real liberties) Example: In figure 16, the block b1 has 3 quasi-liberties (coinciding with its real liberties since none of the points surrounding b1 are circles (shadow stones)). The blocks b2 and b3 have 3 and 2 quasi-liberties, respectively. Using the concept of quasi-liberties, the inversion rule can be stated: n Inversion rule: Consider a λa -tree with value 1 or 0.
Zone made by the inversion rule Now consider figure 18, where white has just played the λ -move white 2, disturbing 3 2 the threatened λa -tree of figure 15. To find candidates for the next black λ -move, the 2 1 0 2 now failing λa -tree is played out, and all those λ -moves (and the λ - and λ -moves 2 generating those λ -moves) are recorded. The shadow of these stones is shown as circles in figure 20. Using the inversion rule, the relevancy zone would look like figure 20. This seems * to be a safe bet for a R -zone containing the true R-zone of black disturbance-moves 3 (black λ -moves following white 2 in figure 18).
The word abstract in our algorithm means that the moves are selected using abstract properties of the objects of the games, such as the liberties of the strings. The second section describes the capture game and its relation to other sub-games of Go. The third section uncovers our search algorithm. The fourth section explains what is the abstract analysis of games that enables Abstract Proof Search. In the fifth section we invalidate the widely accepted knowledge among Go programmers that the number of liberties is a good heuristic for the capture game, we show that the capture game is more subtle and that using too simple heuristics can be harmful.