This dissertation presents a novel and efficient multiple objects tracking technique dealing long-term and complete occlusion. The technique is based on a new low cost object appearance model to associate objects. This work is primarily focused on the improvement of resource utilization aspects, targeting real-time embedded applications with limited resources. Moreover, a comparative accuracy analysis is also performed to ensure that the proposed work is in close agreement with state of the art methods in terms of accuracy. This dissertation is mainly composed of three contributions. The first contribution presents a K-means based model for object appearance modeling. The appearance model combined with the simple object spatial position is used to infer the objects association/tracking decision. The objects appearance model and temporal spatial position is updated for one to one object/blob association throughout the sequence of video. However, for one-to-many blob/objects associations after the onset of occlusion a statistical distance measure is introduced for object association to deal occlusion. The comparative evaluation of resource utilization on standard datasets shows the superior performance of our approach in terms of computational time and/or memory as compared to the state-of-the-art baseline methods. In our second contribution, a low cost K-means based object appearance model is presented to achieve a faster solution for multiple objects tracking. In our first contribution and the recent literature, the object appearance is updated in every frame. However, there is no need to update the appearance model in every frame as more often it tends not to change. For this purpose, a novel histogram based appearance update model is applied on every detected blob to decide when to update the appearance model. Moreover, the employed histogram based cluster initialization further reduces the overall computational cost as the standard K-means algorithm can take more time to converge due to improper initialization of cluster centroids. The presented low cost model achieves much faster solution as compared to the baseline K-means and GMM based models with comparable memory requirements and accuracy. xi The first two contributions are about realizing a low cost multiple objects tracking method using merge and split approach for occlusion reasoning. The accuracy of the merge and split is compromised during occlusion. However, the emphasis of third contribution is on the improvement of accuracy during occlusion with reasonable resource utilization. In this contribution the K-means based method is extended to straight through approach, which tracks the individual objects despite occlusion thus increasing the accuracy. Low cost shape and appearance models are combined for pixel association during occlusion. Furthermore, two-pass outlier rejection technique is employed to address the issue of outliers. Our approach provides superior accuracy as compared to the state-of-the-art online multiple objects tracking approaches with comparable resource utilization. The prime objective of all the contributions of this dissertation is to provide a resource efficient solution of multiple objects tracking with comparable accuracy to the state of the art. In literature, the main focus of researchers is towards the aim of the accuracy with compromise on the resource utilization aspects of the system. The trending embedded smart cameras have started to replace the conventional PC based surveillance systems due to their low cost and built-in intelligence. To achieve real time solution with limited available resource, smart cameras require efficient algorithms with minimum resource utilization. With efficient resource utilization, the multiple objects tracking algorithms proposed in this dissertation, provides very strong grounds for the development of smart camera based real time surveillance solution.
Taking an ‘analogical’ approach to the issue, this study reads the saga of Atiya Fyzee’s relationship with Shibli Nomani and Allama Iqbal as a plausible allegory of the transforming cultural relationship of the Muslims of the subcontinent with English (in what this term comes to mean as a language, as a discipline of studies, and as a synecdoche of Western culture). The history of this cultural interaction since the British colonization I have divided into three broad phases: the initial, the middle, and the present. The initial phase I earlier dealt with by exploiting Sheikh Muhammad Ikram’s analogy, later employed by Nasir Abbas Nayyar, that Shibli’s attitude towards English was the same as his attitude towards his step-mother at home. English, in other words, was a stepmother for Shibli, and for the generations represented through his figure in this early phase of cultural interaction of the Muslims of the subcontinent with the language. The present paper focuses on how one can analogically read in the personal histories of the representative figures of this culture the stories of how in the subcontinent the larger cultural reception of English gradually changed from being treated as a ‘step-mother’(and hence forging with her a relationship of cultural exchange) to being treated as a ‘social butterfly’ or a ‘social sweetheart’, as a symbol of liberal humanist high culture, and how such terms of cultural engagement with English were unacceptable to both Shibli and Iqbal. The paper closes on how even this image of English as high culture gradually dissolved with the cultural disintegration wrought by an ever-increasing and relentless consumerist culture in the postcolonial times.
Good macroeconomic policies can be transformed into good economic performance. Fiscal policies whether public expenditures or revenues can actively be used to improve economic performance by the governments of the developing economies. The study has been constructed to explore the effects of fiscal variables in aggregate as well as in disaggregated form on private investment and economic growth. It covers the period from 1972 to 2007 in the context of Pakistan. Enhancement of private investment and fostering of economic growth in the economy will not only bring macroeconomic stability but also generate employment in the long-run. After establishing the integration order of variables, Autoregressive Distributed Lag (ARDL) approach to co-integration has been employed to find the long-run effects as well as short-run effects. In the first step, existence of long-run relationship has been determined by using bounds testing approach. Long-run coefficients and error correction term has been obtained in the second step. Modified accelerator model and neo-classical model have been used to find the empirical relationship between fiscal variables and private investment. The outcomes under different estimators of the accelerator investment model seem to largely confirm that fiscal variables play some role to stimulate private investment though some of theses variables have been found to be insignificant statistically. The results of the neoclassical model are largely in agreement to those under the accelerator model in terms of signs and significance. Both confirm the hypothesis of crowding-in effects of public investment in different sectors though weak statistically. Further, in order to find the impact of fiscal policy on economic growth, endogenous growth model has been used. The results imply that public expenditures are complementary to economic growth, though with weaker magnitude. Similarly, different components of taxation have weak and mixed effects on economic growth but taxes in aggregate form, though weak, have positive contribution towards economic growth.