Presents the theory and algorithmic considerations in using sparse models for image understanding and computer vision applications. To this end, algorithms for obtaining sparse representations and their performance guarantees are discussed. Approaches for designing overcomplete, data-adapted dictionaries to model natural images are also described.
Presents the theory and algorithmic considerations in using sparse models for image understanding and computer vision applications. To this end, algorithms for obtaining sparse representations and their performance guarantees are discussed. Approaches for designing overcomplete, data-adapted dictionaries to model natural images are also described.