Learn More
Local features have the ability to overcome the major drawback of traditional, holistic object detection approaches, because they are inherently invariant to geometric deformation and pose; in addition scale and rotation invariance can be easily achieved as well. However, the selection of discriminative feature locations and local descriptions is a complex(More)
Personalized multimedia content which suits user preferences and the usage environment, and as a result improves the user experience, gains more importance. In this paper, we describe an architecture for personalized video adaptation and presentation for mobile applications which is guided by automatically generated annotations. By including this annotation(More)
Background subtraction is a widely used technique for video object segmentation. Its main drawback is its constraint to video from a static camera. Several proposals have been made to extend background model generation to camera movement, while few approaches can cope with many degrees of freedom in camera motion. We present a method to generate background(More)
This paper presents a new self-adapting and content-sensitive optimization technique for the H.264/AVC in-loop deblocking filter [1], focussing on the visual enhancement of the perceived reconstruction quality. Performed frame-wisely at the encoder side, the proposed algorithm first identifies visually important image regions in the currently decoded and(More)
In this paper we present a generic video object tracking scheme that combines a feature point tracker with a graph cut based image segmentation algorithm. The system deals with deformable objects in dynamic scenes and is initialized by a ground truth of the object region in the first frame. Hence colour models representing the appearance of the foreground(More)
In this paper we present a method for the detection of wrong feature correspondences in a local feature based object detection system. Common visual objects in different images share not only similar local features but also a similar spatial layout of their features. We will utilize this fact in order to distinguish between correct and wrong feature(More)
  • 1