Guo, Jing-Ming; Chang, Cheng-Hsin; Lee, Hua; Radzicki, Vincent; Department of Electrical Engineering, National Taiwan University of Science and Technology; Department of Electrical and Computer Engineering University of California, Santa Barbara (International Foundation for Telemetering, 2017-10)
      Target detection and tracking is one of the most common applications of video systems. The requirement of processing time due to the computation complexity has been the most challenging element for these operations. To achieve computation efficiency, video synopsis is one of the most promising approaches. Video synopsis is a technique that focuses on the removal or reduction of spatial and temporal redundancies, while maintaining important activities in the original video. In this paper, a new video synopsis scheme is introduced. Major characteristics of this technique include efficient background subtraction, superior processing speed, and effective object comparison.

      Lee, Hua; Radzicki, Vincent; UCSB, Dept Electrical & Comp. Eng. (International Foundation for Telemetering, 2017-10)
      This paper is the summary of a sequence of research tasks in the area of 3D bearing-angle estimation for UUV homing and docking exercises. The main focus is to simplify the concept as well as computation efficiency of the homing and docking tasks, by elevating the estimation modality from the conventional twin-receiver configuration to the 2D circular arrays. The objective is to utilize the multi-element receiver array for the entire navigation procedure, including bearing-angle estimation, optimal path planning, and high-precision docking.
    • PUREmodules: An IoT Development Method to Simplify Prototype Hardware

      Afzal, Furqaan; Rodriguez, Michael; Lee, Kyle; Ono, Sashi; Lee, Hua; Radzicki, Vincent; Pure Engineering; Department of Electrical and Computer Engineering (International Foundation for Telemetering, 2017-10)
      Conventional hardware development of sensor systems can be complex and tedious due to the time-consuming procedures of prototyping the physical hardware and the lack of firmware examples for testing and evaluation. In this paper, we introduce the concept of a new development process in the format of one single core module with a standardized interface so that a large number of sensors may be connected easily in an ad-hoc manner. The sensors can then be programmed with standard development tools and processes. The concept of the design modules enables effective and rapid prototyping of hardware implementations without prior knowledge of the low-level details of the hardware components. With this capability, sensors can be connected to a core module for rapid development of low-cost high-performance devices.

      Rajagopal, Abhejit; Radzicki, Vincent; Chandrasekaran, Shivkumar; Lee, Hua; UCSB, Dept Electrical & Comp. Eng. (International Foundation for Telemetering, 2017-10)
      Traditional target detection pipelines involve two sequential steps: the formation of a range-profile or likely-image, and the classification of likely targets within that image. Although it has been shown that target tracking in the RaDAR image-domain can be unnecessarily noisy, with more accurate and efficient implementations involving a direct analysis of the measured wavefield, image formation remains a desirable output in many applications due to its highly descriptive and interpretable nature. In this paper, we outline a mechanism for formalizing and accelerating this procedure in application-specific use cases. Enabled by recent advances in deep learning, we present a pipeline for automatically selecting an “optimal” filtered back-projection model, forming a likelyimage, and performing target recognition and classification. The architecture allows practitioners to track and optimize the flow of information throughout the pipeline, enabling applications that utilize only intermediate outputs of the algorithm.