Person tracking using motion detection and optical flow

Person tracking systems to date have either relied on motion detection or optical flow as a basis for person detection and tracking. As yet, systems have not been developed that utilise both these techniques. We propose a person tracking system that uses both, made possible by a novel hybrid optical flow-motion detection technique that we have developed. This provides the system with two methods of person detection, helping to avoid missed detections and the need to predict position, which can lead to errors in tracking and mistakes when handling occlusion situations. Our results show that our system is able to track people accurately, with an average error less than four pixels, and that our system outperforms the current CAVIAR benchmark system.

Doing Time in the Retail Industry

This paper uses survey data to explore employee satisfaction with working time arrangements within a large supermarket chain in Queensland. The findings confirm those in the literature that employees have a diverse range of working time preferences, and that employees will be more satisfied if those preferences are met by their employer. In general, many full-time employees wanted shorter hours and a sizeable proportion of part-time employees wanted longer working hours. This paper is a preliminary attempt at teasing out the explanations behind working time preferences.