CCTV scene perspective distortion estimation from low-level motion features

Our aim is to estimate the perspective-effected geometric distortion of a scene from a video feed. In contrast to most related previous work, in this task we are constrained to use low-level spatiotemporally local motion features only. This particular challenge arises in many semiautomatic surveillance systems that alert a human operator to potential abnormalities in the scene. Low-level spatiotemporally local motion features are sparse (and thus require comparatively little storage space) and sufficiently powerful in the context of video abnormality detection to reduce the need for human intervention by more than 100-fold. This paper introduces three significant contributions. First, we describe a dense algorithm for perspective estimation, which uses motion features to estimate the perspective distortion at each image locus and then polls all such local estimates to arrive at the globally best estimate. Second, we also present an alternative coarse algorithm that subdivides the image frame into blocks and uses motion features to derive block-specific motion characteristics and constrain the relationships between these characteristics, with the perspective estimate emerging as a result of a global optimization scheme. Third, we report the results of an evaluation using nine large sets acquired using existing closed-circuit television cameras, not installed specifically for the purposes of this paper. Our findings demonstrate that both proposed methods are successful, their accuracy matching that of human labeling using complete visual data (by the constraints of the setup unavailable to our algorithms).

Dealing constructively with negatively evaluated emotional situations: the key to understanding the different reactions of teachers with high and low levels of emotional intelligence

Recent work on the distinctive features of emotions appraised as either negative or positive has links to the investigation of differences in levels of emotional intelligence. In a study with experienced teachers as participants, it was found that emotional reactions to positive or negative situations was moderated by level of emotional intelligence. The reactions to positively charged emotional situations involving students and peers were similar for teachers with high and low levels of emotional intelligence, although the low level group showed somewhat lower likelihood of making an “emotionally intelligent” response compared to the high level group. A much sharper contrast in response likelihood was found for negatively charged emotional situations involving students and peers. Teachers with high levels of emotional intelligence responded quite differently to those with low levels of emotional intelligence. The results indicate the prospect of clarifying a neglected area of exploration of differences in the likely behaviour of teachers differing in levels of emotional intelligence.

Interpersonal trust and formal controls in low systemic trust societies

This study is concerned with the role of interpersonal trust in management control. On the basis of a questionnaire survey and interviews of senior managers from business organisations in sri lanka, the study explores the control behaviour of superior managers when they trust or distrust their subordinates. Sri lanka, a society in which the dependence on interpersonal trust is high, was chosen for the study to maximise the effect of interpersonal trust.

The findings of this study indicate that a superior's high trust in a subordinate is associated with a low level of monitoring, a high level of social interactions, and a low reliance on formal controls. In contrast, a superior's low level of trust in a subordinate is associated with a high level of monitoring, a low level of social interactions, and a high reliance on formal controls. Because the data emanate from experienced senior managers, these findings are at least indicative of control behaviour of superior managers in sri lanka and possibly of similar countries in asia. An understanding of the control behaviour of managers in this region is particularly important for designing and implementing effective controls systems for firms, subsidiaries, branches or joint-ventures operating in the region.

Recognising and monitoring high-level behaviours in complex spatial environments

The recognition of activities from sensory data is important in advanced surveillance systems to enable prediction of high-level goals and intentions of the target under surveillance. The problem is complicated by sensory noise and complex activity spanning large spatial and temporal extents. This paper presents a system for recognising high-level human activities from multi-camera video data in complex spatial environments. The Abstract Hidden Markov mEmory Model (AHMEM) is used to deal with noise and scalability The AHMEM is an extension of the Abstract Hidden Markov Model (AHMM) that allows us to represent a richer class of both state-dependent and context-free behaviours. The model also supports integration with low-level sensory models and efficient probabilistic inference. We present experimental results showing the ability of the system to perform real-time monitoring and recognition of complex behaviours of people from observing their trajectories within a real, complex indoor environment.

Discrete event simulation enabled high level emulation of a distribution centre

Emulation facilitates the testing of control systems through the use of a simulation model. Typically emulation has focused on low level control, to ensure that resources within a system are commissioned correctly. Higher level control that deals with complex issues such as throughput, in-system time and stacking, has not received as much attention. In this paper, a higher level agent-based emulation framework was proposed. Then an emulation model for a distribution centre is described that can test distribution centre level algorithms directly. This methodology also allows playback of real world operations, making it an ideal tool to analyse problems with performance of commissioned systems.