Presentation on theme: "An Effective Dynamic Gesture Recognition System Based on the Feature Vector Reduction for SURF and LCS PABLO BARROS, NESTOR JÚNIOR, JUVENAL BISNETO, BRUNO."— Presentation transcript:
An Effective Dynamic Gesture Recognition System Based on the Feature Vector Reduction for SURF and LCS PABLO BARROS, NESTOR JÚNIOR, JUVENAL BISNETO, BRUNO FERNANDES, BYRON BEZERRA, SÉRGIO FERNANDES. ESCOLA POLITÉCNICA DE PERNAMBUCO - UNIVERSIDADE DE PERNAMBUCO - BRASIL
Contour Identification Hand Contour Identification
LCS - Local Contour Sequence Feature Vector Calculation Find the top first point of the image Order the points in clockwise. Calculate distance of a line formed by two points, ℎ [−(−1)⁄2] and ℎ [−(+1)⁄2], and h[i].
Speed Up Robust Features - SURF Integral Image Find Interest Points Describe Interest Points Intensity Direction Descriptors
Convexity Approach Douglas Peucker Algorithm Select the two most distant points. Verify if there is vertex near than a distance T, if there is, remove it. Recursively do it again with all the points.
Convexity Approach Sklanky´s Algorithm Find a convex vertex. Rename the other vertex in clockwise, starting with p0. If p0, p1 and p2 turn right: Put p0 after p2. Update p0, p1 and p2. Else: Put p1 before p0. Remove p1. Update p0, p1 and p2. Repeat until p0 is the initial vertex and p0, p1 and p2 turns right. For each pair of points draw a line and find the most distant point.
Convexity Local Contour Sequence Calculate distance Adaptation of LCS Use the two external points to draw the line. Use the inner point to calculate distance. (a) LCS. (b) SuRF interest points. (c) CLCS. (d) CSURF
Classification Module Elman Recurrent Neural Network Hidden Markov Model Dynamic Time Warping
Results Convexity Approach Methodology Run 30 times Validation (1/3 for test and 2/3 for training)
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