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A pedestrian detector is provided with the algorithm models of active shape (ASM), with the stages: training (PDM) and adjustment (ASM). With PDM, 50 landmarks are marked, and gray profiles are extracted in the silhouette of each pedestrian in 137 images (pedestrian1 and pedestrian2) applying the variation modes (PCA). The contribution of this work is the adjustment and detection of a pedestrian despite the variations. At the end, the results evaluated with leave one out in each 1 080 × 720 pixels image and with the mean square error (MSE) metric, a total average of 12.7 pixels is obtained in the error distance between the original landmarks and the estimated landmarks.

Detección de peatones con variaciones de forma al caminar con Modelos de Forma Activa