Object Classification with Joint Projection and Low-rank Dictionary Learning

5 Dec 2016 Homa Foroughi Nilanjan Ray Hong Zhang

For an object classification system, the most critical obstacles towards real-world applications are often caused by large intra-class variability, arising from different lightings, occlusion and corruption, in limited sample sets. Most methods in the literature would fail when the training samples are heavily occluded, corrupted or have significant illumination or viewpoint variations... (read more)

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