Abstract: A relationship extracting apparatus acquires event information that indicates features of an event of interest, determine target duration based on one or more features of the event of interest, and extract one or more action-related relationships that exist during the target duration from object relationships information. The object relationship information indicates two or more action-related relationships between objects in association with time at which or during which the action-related relationship exists.

Abstract: An event detecting apparatus acquires one or more video data, and generates, from the one or more video data, object relationship information that indicates two or more action-related relationships between objects. The event detecting apparatus acquires an event information that indicates an event of interest by a sequence of action-related situations at least one of which represents a situation in which a specific action is taken by a specific subject. The event detecting apparatus determines whether or not the event of interest occurs based on the object relationship information and the event information.

Abstract: This disclosure concerns image quality assessment. In particular, there is described a computer implemented method, software, and computer for assessing the quality of an image. For example but not limited to, quality of the image of a face indicates the suitability of the image for use in face recognition. The invention comprises determining (112) a similarity of features of two or more sub-images of the image (608) to a model (412) of the object which is based on multiple training images (612) of multiple different objects of that type. The model (412) is comprised of sub-models (406) and each sub-model (406) corresponds to a sub-image of the image (608). Determining similarity is based on the similarity of features of each sub-image to features modelled by the corresponding sub-model. It is an advantage that no input parameters are required for quality assessment since the quality of the image can be determined from only the similarity between the image and the same, therefore single generic, model.

Abstract: The disclosure concerns face recognition systems. The aim is to identify candidate matching images to a probe image. There is provided methods, software and computer system to select (22, 24) a method of matching images from two or more methods of matching images based on an underlying resolution (20) of the probe image (8). Comparing two images of differing resolutions is common in surveillance environments. To alleviate this degradation, the method advantageously dynamically selects the most appropriate matching method for a probe image. The disclosure also provided methods to determine the underlying resolution of a probe (8) or gallery image (14).

Abstract: This disclosure concerns image quality assessment. In particular, there is described a computer implemented method, software, and computer for assessing the quality of an image. For example but not limited to, quality of the image of a face indicates the suitability of the image for use in face recognition. The invention comprises determining (112) a similarity of features of two or more sub-images of the image (608) to a model (412) of the object which is based on multiple training images (612) of multiple different objects of that type. The model (412) is comprised of sub-models (406) and each sub-model (406) corresponds to a sub-image of the image (608). Determining similarity is based on the similarity of features of each sub-image to features modelled by the corresponding sub-model. It is an advantage that no input parameters are required for quality assessment since the quality of the image can be determined from only the similarity between the image and the same, therefore single generic, model.

Abstract: The disclosure concerns face recognition systems. The aim is to identify candidate matching images to a probe image. There is provided methods, software and computer system to select (22, 24) a method of matching images from two or more methods of matching images based on an underlying resolution (20) of the probe image (8). Comparing two images of differing resolutions is common in surveillance environments. To alleviate this degradation, the method advantageously dynamically selects the most appropriate matching method for a probe image. The disclosure also provided methods to determine the underlying resolution of a probe (8) or gallery image (14).