Video Analysis via Nonlinear Dimensionality Reduction Technique

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Presentation transcript:

Video Analysis via Nonlinear Dimensionality Reduction Technique Yi Li Colin Zheng

Roadmap Nonlinear Dimensionality Reduction Video Analysis LLE Isomap A trajectory thorough an image space Low dimension embedding

Problem Setting Input Analysis Output Image Sequence: each image is a point in a high dimensional space Analysis Use nonlinear dimensionality reduction technique Use L2 Norm as distance metric Output A trajectory in a low dimensional space

Bird Flying Sequence Input Tracking

Embedding

Scaling vs. non-scaling

Resized Bird

Temporal Super-Resolution

Ellipse Fitting

Running Original Input

LLE Embedding

Isomap Embedding

Fitting Input Input Original Output

Conclusion A powerful tool to discover the intrinsic low dimensionality in video trajectory Future Work Better distance metric More applications