Abstract: A video monitoring support apparatus 10 provides support to make settings in a new monitoring camera in a video monitoring system in which discriminators are used to detect objects. The video monitoring support apparatus 10 includes a region acquisition unit 11 that acquires, from the video monitoring system, information regarding a discriminator application region that is set to an existing monitoring camera in order to detect an object with a discriminator, and a region setting unit 12 that uses the acquired information to set, to the video monitoring system, a discriminator application region of the new monitoring camera.

Abstract: An object detection apparatus is provided with a discriminator applier and a candidate area calculator. The discriminator applier applies a discriminator which detects an object to images acquired in past and calculates object detection information including at least location information of the object detected by the discriminator, in a learning phase. The candidate area calculator performs a machine-learning by use of the object detection information and calculates object candidate area information including at least information specifying a candidate area in which the object may appear in an image.

Abstract: A video monitoring support apparatus 10 provides support to make settings in a new monitoring camera in a video monitoring system in which discriminators are used to detect objects. The video monitoring support apparatus 10 includes a region acquisition unit 11 that acquires, from the video monitoring system, information regarding a discriminator application region that is set to an existing monitoring camera in order to detect an object with a discriminator, and a region setting unit 12 that uses the acquired information to set, to the video monitoring system, a discriminator application region of the new monitoring camera.

Abstract: An object detection apparatus is provided with a discriminator applier and a candidate area calculator. The discriminator applier applies a discriminator which detects an object to images acquired in past and calculates object detection information including at least location information of the object detected by the discriminator, in a learning phase. The candidate area calculator performs a machine-learning by use of the object detection information and calculates object candidate area information including at least information specifying a candidate area in which the object may appear in an image.

Abstract: A column-store database management system includes a storage unit that stores a predetermined data structure, and a database management unit. The data structure corresponds to table-format data expressed as arrays of records including field values of each field, and includes, for each field, a value list in which field values in the field are stored corresponding to field value numbers uniquely specifying the field values, and a value number array including information designating the field values in the record order. The storage unit stores a first data structure that corresponds to first table-format data and includes a value list and a value number array of the first field. When the database management unit generates a second data structure from the second table-format data, it generates a value list of the first field of the second data structure using the value list of the first field of the first data structure.