Topic
Object (computer science)
About: Object (computer science) is a research topic. Over the lifetime, 106024 publications have been published within this topic receiving 1360115 citations. The topic is also known as: obj & Rq.
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11 Sep 2006TL;DR: In this article, a method for determining an intensity value of an interaction with a computer program is described, which includes capturing an image of a capture zone, identifying an input object in the image, identifying the initial value of a parameter of the input object, capturing a second image of the capture zone and identifying a second value of the parameter.
Abstract: A method for determining an intensity value of an interaction with a computer program is described. The method and device includes capturing an image of a capture zone, identifying an input object in the image, identifying an initial value of a parameter of the input object, capturing a second image of the capture zone, and identifying a second value of the parameter of the input object. The parameter identifies one or more of a shape, color, or brightness of the input object and is affected by human manipulation of the input object. The extent of change in the parameter is calculated, which is the difference between the second value and the first value. An activity input is provided to the computer program, the activity input including an intensity value representing the extent of change of the parameter. A method for detecting an intensity value from sound generating input objects, and a computer video game are also described. A game controller having LEDs, sound capture and generation, or an accelerometer is also described.
268 citations
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268 citations
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17 Jun 2006
TL;DR: The Implicit Shape Model for object class detection is combined with the multi-view specific object recognition system of Ferrari et al. to detect object instances from arbitrary viewpoints.
Abstract: We present a novel system for generic object class detection. In contrast to most existing systems which focus on a single viewpoint or aspect, our approach can detect object instances from arbitrary viewpoints. This is achieved by combining the Implicit Shape Model for object class detection proposed by Leibe and Schiele with the multi-view specific object recognition system of Ferrari et al. After learning single-view codebooks, these are interconnected by so-called activation links, obtained through multi-view region tracks across different training views of individual object instances. During recognition, these integrated codebooks work together to determine the location and pose of the object. Experimental results demonstrate the viability of the approach and compare it to a bank of independent single-view detectors
268 citations
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31 Aug 1999TL;DR: In this article, an abstraction factory pattern in a client/server architecture receives and transforms data into a plurality of concrete objects, each of which is associated with an abstract interface, and a map of the association between the concrete objects and the abstract interface is created.
Abstract: An abstraction factory pattern in a client/server architecture receives and transforms data into a plurality of concrete objects. Each of the concrete objects is associated with an abstract interface. A map of the association between the concrete objects and the abstract interface is created. When a request is received from the client (which includes an identifier for one of the concrete objects and an identifier for the abstract interface) the map on the server is consulted to locate the concrete object that has been identified. Then, an abstract object is created that corresponds to the located concrete object such that the abstract object serves as a handle, generically manipulable by the client/server architecture. The invention represents a way to encapsulate diversity such that only those parts of the system that need to understand the difference between two objects have to deal with those differences.
267 citations