In this talk, I will talk of two problems in visual recognition. In the first part, I will talk about the problem of low resolution face recognition. This problem can happen in many scenarios like surveillance where the probe images are low resolution, but a high resolution gallery image is available. I will describe a synthesis based approach for low resolution recognition and demonstrate results on different face datasets. In the second part, I will describe a new analysis framework for sparse coding which has recently started getting attention. I will describe its application to various recognition problems and also demonstrate that its more efficient than standard sparse coding framework.