Video Feature Extraction Based on Modified LLE Using Adaptive Nearest Neighbor Approach

( Vol-1,Issue-6,September 2015 )

Author(s): Preksha Bohra, Sunil Joshi

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Page No: 21-24
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Keywords:

Feature extraction, Frames, Images, LLE, ISOMAP, Manifold, PCA, Video.

Abstract:

Locally linear embedding (LLE) is an unsupervised learning algorithm which computes the low dimensional, neighborhood preserving embeddings of high dimensional data. LLE attempts to discover non-linear structure in high dimensional data by exploiting the local symmetries of linear reconstructions. In this paper, video feature extraction is done using modified LLE alongwith adaptive nearest neighbor approach to find the nearest neighbor and the connected components. The proposed feature extraction method is applied to a video. The video feature description gives a new tool for analysis of video.

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