In many surveillance applications, the cameras are placed at overhead heights for human identification. In such real-world scenarios, the person of interest might be walking away from the camera and the only information available is 'image of the person's head'. In this research, we investigate the usage of head images for person recognition and propose it as a soft-biometric modality. With its viability for human recognition, application of head images can also be extended with other face recognition algorithms for surveillance. We propose a head image database pertaining to 103 subjects with more than 600 images. In addition to the database, we propose a framework for head image-based person verification. As a pre-processing stage, the framework includes evaluation of two segmentation algorithms. We also perform benchmarking evaluations of various texture, key-point, and learning-based representation algorithms and establish the baseline results. The experiments suggest that head images can be effectively used to ascertain human identity and the availability of this database could pave further research in this field. © 2018 IEEE.