Alex Lopes Pereira
Technological Institute of Aeronautics, Sao Jose dos Campos, Brazil
Title: Patch-based local histograms and contour estimation for static foreground classification
Biography
Biography: Alex Lopes Pereira
Abstract
This speech is about an approach to classify static foreground blobs in surveillance scenarios. Possible application is the detection of abandoned and removed objects. In order to classify the blobs we developed two novel features based on the assumption that the neighborhood of a removed object is fairly continuous. In other words, there is a continuity, in the input frame, ranging from inside the corresponding blob contour to its surrounding region. Conversely, it is usual to find a discontinuity, i.e. edges, surrounding an abandoned object. We combined he two features to provide a reliable classification. In the first feature, we use several local histograms as a measure of similarity instead of previous attempts that used a single one. In the second, we developed an innovative method to quantify the ratio of the blob contour that corresponds to actual edges in the input image. A representative set of experiments shows that the proposed approach can outperform other equivalent techniques published recently.