The developed method combines surrounding image sampling, saliency map, self-organizing map neural network, k-Means segmentation and similarity measurement.
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We present in this paper an SOM-based k-means method (SOM-K) and a further saliency map-enhanced SOM-K method (SOM-KS). In SOM-K, pixel features of intensity ...
Conference Place, Changsha, China ; Author of Source, Springer Verlag ; Abstract, In this paper, a new method is presented for long-term object tracking in ...
Abstract. In this paper, a new method is presented for long-term object track- ing in surveillance videos. The developed method combines surrounding image.
The developed method combines surrounding image sampling, saliency map, self-organizing map neural network, k-Means segmentation and similarity measurement.
Jul 6, 2011 · K-means is a subset of Self-Organizing Maps (SOM). K-means is strictly an average n-dimensional vector of the n-space neighbors. SOM is similar ...
Missing: Object Tracking Saliency
In this paper, a new method is presented for long-term object tracking in surveillance videos. The developed method combines surrounding image sampling, ...
Segmentation refers to the process of partitioning a digital image into multiple segments known as super-pixels. Image segmentation is typically used to ...
Missing: Tracking | Show results with:Tracking
Sep 26, 2016 · The idea behind a SOM is that you're mapping high-dimensional vectors onto a smaller dimensional (typically 2-D) space.
Abstract. We introduce a novel view-based object representation, called the saliency map graph (SMG), which captures the salient regions of an.