In view of the continuous efforts by the automotive fraternity, for achieving traffic safety, detecting pedestrians from image/video has become an extensively researched topic in recent times. The task of detecting pedestrians in the urban traffic scene is complicated by the considerations involving pedestrian figure size, articulation, fast dynamics, background clutter, etc. A number of methods using different sensor technologies have been proposed in the past for the problem of pedestrian detection. To limit the scope, this paper reviews the techniques involved in day-time detection of pedestrians, with emphasis on the methods making use of a monocular visible-spectrum sensor. The paper achieves its objective by discussing the basic framework involved in detecting a pedestrian, while elaborating the requisites and the existing methodologies for implementing each stage of the basic framework. Due to the multiple datasets used across literature, a comparative study of the available detection techniques is intricate. However, the most successful methods for each stage have been highlighted, based on the literature reviewed. The paper concludes with a discussion of the open issues and future trends in the field of pedestrian detection. The assessment made in this work aims to aid in beginning from where the others have left, to avoid re-inventing the wheel.