Objectives: To establish a pattern tracking based motion estimation algorithm for the stereovision based system and to investigate the effect of threshold value (Thv), size and population of patterns on the pattern tracking value. Methods: Proposed motion estimation algorithm correlates the set of motion frames captured from two high speed cameras configured in stereovision system. The correlation scheme was based on grayscale pattern tracking in moving frames. Pattern development and

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... n algorithms were developed. A spherical object was given small random displacements and the motion was captured using stereovision system. The effectiveness of algorithm is evaluated with the pattern tracking value which should be close to 1 for perfect pattern match. Findings: The correlation results indicate that pattern tracking value were found to be 0.920 and 0.899 for left and right cameras respectively when the threshold value (>10) and size 10 pixels are considered with high population (200 patterns). With the increase in pattern size, the pattern tracking value decreased. Another study revealed that pattern tracking value was comparatively higher when the pattern population was maximum (200 patterns). The pattern tracking value again decreased when the threshold value (>15) is considered. It was concluded that pattern size of 10 pixels with threshold value (>10) is more pronounced for motion estimation. The proposed algorithm is verified for the 3D displacements of a rectangular plate mounted on XYZ translation stage. The pattern tracking values were 0.97, 0.95, 0.96 and 0.96, 0.94, 0.95 for X, Y and Z displacements respectively. The correlation algorithm is also coupled with the compression technique using wavelet based data compression. Novelty/Applications: The proposed algorithm can be efficiently applied for both in plane and out of plane motion estimation. The algorithm can provide constructive outcomes for small motion prediction with proper selection of pattern size and threshold value.