Abstract: Video surveillance systems are used to monitor public places, streets, buildings, cities and other premises or surroundings and comprise a multitude of cameras which are monitoring relevant points in the surroundings. One of the problems of surveillance systems is, that the multitude of cameras produce a large amount of video data to be monitored, which requires a lot of human observers resulting in high personnel costs.

Abstract: Surveillance systems are used in general to monitor buildings, public places, traffic and the like. These systems conventionally comprise a plurality of surveillance cameras producing a large amount of video data. The video data is viewed on-line or recorded and searched through off-line. Especially in the latter case there is a strong need to improve the search speed due to the large amount of the video data.

Abstract: A video retrieval system is proposed that retrieves trajectory data from a database as a response to a search query. The search query is formulated on the basis of a search trajectory, which is represented as a plurality of search segments. Minimum hounding areas are generated, whereby the plurality of the minimum hounding areas cover the search trajectory or at least one of the search segments. The video retrieval system accesses the database by using at least one of the minimum bounding areas as a query area, whereby the minimum bounding areas of the plurality of bounding areas are arranged overlap-free and/or adjacently or with a search trajectory independent overlap.

Abstract: Video systems are widely used in the field of surveillance of buildings, traffic, private homes, supermarkets and the like. For some applications it is useful to save the video information for a later access or analysis. As the saved data volume increases with the number of video cameras of a video system and the recorded time there is a need for video databases, which allow a fast searching for relevant video information.

Abstract: Surveillance systems are used in general to monitor buildings, public places, traffic and the like. These systems conventionally comprise a plurality of surveillance cameras producing a large amount of video data. The video data is viewed on-line or recorded and searched through off-line. Especially in the latter case there is a strong need to improve the search speed due to the large amount of the video data.

Abstract: Nowadays, video cameras are often used for monitoring areas under surveillance. For monitoring more complex surroundings a plurality of video cameras are commonly employed, whereby the resulting data from the plurality of video cameras is viewed on-line or stored in data-bases and checked off-line. With a growing number of video cameras also the amount of the stored video data is increasing rapidly, which finally results in an enormous effort to search through the video data on- or off-line in case a time instance or location of a certain interesting event is unknown. Improvements are achieved by using systems for content-based indexing and retrieval of video data.

Abstract: Video surveillance systems are used to monitor public places, streets, buildings, cities and other premises or surroundings and comprise a multitude of cameras which are monitoring relevant points in the surroundings. One of the problems of surveillance systems is, that the multitude of cameras produce a large amount of video data to be monitored, which requires a lot of human observers resulting in high personnel costs.

Abstract: Video systems are widely used in the field of surveillance of buildings, traffic, private homes, supermarkets and the like. For some applications it is useful to save the video information for a later access or analysis. As the saved data volume increases with the number of video cameras of a video system and the recorded time there is a need for video databases, which allow a fast searching for relevant video information.

Abstract: Memory capacity requirements in systems-on-chip have led to the use of DRAM-based memory devices. A property of these devices is the burst-oriented access of data. These bursts can be considered as successive non-overlapping blocks of data in the memory that can only be accessed as an entity. Therefore, when a data entity is accessed, it is always aligned with a grid that has the same granularity as the data entities. The size of the data entities is determined by the length of the burst and the width of the memory bus. A way to refine the alignment grid although the amount of bytes per burst remains equal is proposed. A solution for a memory controller is presented that features separate address busses for several parallel memory devices instead of a shared address bus. Due to the refined alignment grid, the amount of transfer overhead can be reduced significantly. The drawback of the invention for off-chip memory devices is the increase in the system costs and the power dissipation.

Abstract: A method of storing data-elements (1-12) into a memory device (118) comprises: a first grouping step of grouping the data elements (1-12) into a first arrangement of sets (102-108) of data elements (1-12); a first writing step of writing first copies of the respective data elements (1-12) into data-units (120), whereby first copies of those data elements (1,2,3) which belong to a first one (102) of the sets of the first arrangement are written into a first data-unit (120); a second grouping step of grouping the data elements (1-12) into a second arrangement of sets (110-116) of data elements (1-12); and a second writing step of writing second copies of the respective data elements (1-12) into further data-units (122), whereby second copies of those data elements (1,5,9) which belong to a first one (110) of the sets of the second arrangement are written into a second data-unit (122) of the further data-units (122).