Ulm, Univ., Diss., 2008.

Thesis (Ph.D.)--University of Western Australia, 2007. / "WATRI (Western Australian Telecommunications Research Institute)"

Thesis (Ph. D.)--University of Texas at Austin, 2004. / Supervisor: Aloysius K. Mok. Vita. Includes bibliographical references.

Thesis (M.S.)--University of Wisconsin--Madison, 1983. / Typescript. eContent provider-neutral record in process. Description based on print version record.

Thesis (Ph. D.)--University of Texas at Austin, 1998. / Vita. Includes bibliographical references (leaves 163-167). Available also in a digital version from Dissertation Abstracts.

This thesis presents a framework for automatic recognition of human actions in un- controlled, realistic video data with fixed cameras, such as surveillance videos. In this thesis, we divide human action recognition into three steps: description, representation, and classification of local spatio-temporal features. The bag-of-features model was used to build the classifier. Fisher Vectors were also studied. We focus on the potential of the methods, with the joint optimization of two constraints: the classification precision and its efficiency. On the performance side, a new local descriptor, called Gradient Boundary Histograms (GBH), is adopted. It is built on simple spatio-temporal gradients, which can be computed quickly. We demonstrate that GBH can better represent local structure and motion than other gradient-based descriptors, and significantly outperforms them on large datasets. Our evaluation shows that compared to HOG descriptors, which are based solely on spatial gradient, GBH descriptor preserves the recognition precision even in difficult situation. Since surveillance video captured with fixed cameras is the emphasis of our study, removing the background before action recognition is helpful for improving efficiency. We first preprocess the video data by applying HOG to detect humans. GBH descriptor is then used at reduced spatial resolutions, which yields both high efficiency and low memory usage; in addition, we apply PCA to reduce the feature dimensions, which results in fast matching and an accelerated classification process. Experiments our methods achieved good performance in recognizing precision, while simultaneously highlighting effectiveness and efficiency.

International Telemetering Conference Proceedings / November 04-07, 1991 / Riviera Hotel and Convention Center, Las Vegas, Nevada / In this paper we present the REAL/STONE Real-Time Tester, a tool for performance evaluation of real-time UNIX operating systems. The REAL/STONE Real-Time Tester is a synthetic benchmark that simulates a typical real-time environment. The tool performs typical real-time operations, such as: (a) reads data from an external source and accesses it periodically, (b) processes data through a number of real-time processes, and © displays the final data. This study can help users in selecting the most-effective real-time UNIX operating system for a given application.

Today’s wireless users expect great things from tomorrow’s wireless networks. These expectations have been fueled by hype about what the next generations of wireless networks will offer. The rapid increase of wireless subscribers increases the quality of services anytime, anywhere, and by any-media becoming indispensable. Integration of various networks such as CDMA2000 and wireless LAN into IP-based networks is required in these kinds of services, which further requires a seamless vertical handoff to 4th generation wireless networks. The proposed handoff algorithm between WLAN and CDMA2000 cellular network is implemented. The results of the simulation shows the behavior of the handoff and the time spent in WLAN or CDMA. The number of weak signal beacons determines whether a handoff is required or not. In this algorithm, traffic is classified into real-time and non real-time services.

In an LTE (Long-Term Evolution) network, HARQ (Hybrid Automatic Repeat reQuest) is used to reduce the error probability of retransmitted packets. However, HARQ cannot guarantee delay constraints for real-time traffic when RBs (Resource Blocks) are allocated improperly. To avoid the retransmitted real-time packets exceeding their delay constraints, we propose an HARQ scheduling scheme based on RTT (Round-Trip-Time) estimation. In this scheme, traffic are classified into real-time and non-real-time queues in which real-time queue are further classified into four sub-queues according to their retransmission times; i.e., the first transmission queue, the first retransmission queue, the second retransmission queue, and the third retransmission queue. For the four real-time queues, we estimate RTT and compute the number of RBs required satisfying the delay constraints. To prevent from starvation of non-real-time traffic, after allocating the RBs for real-time traffic, the remaining RBs are allocated for non-real-time traffic according to their MBR (Minimum Bit Rate). To analyze the proposed scheduling scheme, we build a mathematical model to derive the successful probability of retransmitted packets and the expected value of packet retransmission times. Finally, we compute average packet delay, average packet loss rate, and the throughput for both real-time and none-real-time traffic by varying packet error probability and the delay constraints of real-time traffic.

Graduate