Conference Paper

A core for ambient and mobile intelligent imaging applications

Inst. of Microelectron. Syst., Hannover Univ., Germany;
DOI: 10.1109/ICME.2003.1221538 Conference: Multimedia and Expo, 2003. ICME '03. Proceedings. 2003 International Conference on, Volume: 2
Source: IEEE Xplore

ABSTRACT This paper describes the work in progress of the European IST-2001-34410 CAMELLIA project, which focuses on a platform-based development of a smart imaging core to be embedded in smart cameras. Therefore the work within the CAMELLIA project comprises the specification and implementation of smart imaging applications including the development of required new algorithms and hardware. Based on an existing video encoding architecture for MPEG-4 Simple Profile, the aim is to design a smart imaging core, which is suitable for automotive and mobile communication applications. Thereby the encoding architecture is to be extended with processing units for low- and mid-level smart imaging functions. To indicate the applicability of this platform-based development, a first approach for a motion estimation based background detection using a hardware motion estimation unit is illustrated in this paper. Furthermore, first results employing the background detection to detect moving objects in video sequences using a functional simulator of a video encoding architecture are presented.

  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a modular coprocessor architecture for embedded real-time image and video signal processing. Applications are separated into high-level and low-level algorithms and mapped onto a RISC and a coprocessor, respectively. The coprocessor comprises an optimized system bus, different application specific processing elements and I/O interfaces. For low volume production or prototyping, the architecture can be mapped onto FPGAs, which allows flexible extension or adaption of the architecture. Depending on the complexity of the coprocessor data paths, frequencies up to 150 MHz have been achieved on a Virtex II-Pro FPGA. Compared to a RISC processor, the performance gain for an SSD algorithm is more than factor 70.
    Embedded Computer Systems: Architectures, Modeling, and Simulation, 7th International Workshop, SAMOS 2007, Samos, Greece, July 16-19, 2007, Proceedings; 01/2007
  • [Show abstract] [Hide abstract]
    ABSTRACT: This survey addresses a number of challenges and research areas identified in real time image processing for state-of-the-art hand-held device implementation in networked electronic media. The challenges appear when having to develop and map processing algorithms not only on fading, noisy, and multi-path band limited transmission channels, but more specifically here on the limited resources available for decoding and scalable rendering on battery-limited hand-held mobile devices. Networked electronic media requires scalable video coding which in turn introduces additional degradation. These problems raise some complex issues discussed in the paper. A need to extend, modify and even create new algorithms and tools, targeting architectures, technology platforms, and design techniques as well as scalability, computational load and energy efficiency considerations has established itself as a key research area. A multidisciplinary approach is advocated.
    Journal of Real-Time Image Processing 01/2006; 1:9-23. · 1.16 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: We present an improvement to the object detection scheme of Viola and Jones (2004), using the example of face detection. We present a new kind of visual features that is based on sampling individual pixels within the examined sub-window, instead of comparing the sums of pixel values in rectangular regions. Our features are faster and do not demand the preparation of an integral image, nor variance-normalisation of each sub-window. The result is an improved system that detects faces in quarter-PAL images in only 9 milliseconds per image on a 2.4-GHz pentium computer.
    IJISTA. 01/2007; 2:102-112.

Full-text (2 Sources)

Available from
May 16, 2014