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We present an unsupervised method to estimate the camera orientation angle on monocular video scenes in the H.264 compressed domain. The method is based on the presence of moving objects in the scene. We start by estimating the global camera motion based on the motion vectors present in the stream, detect and track moving objects and estimate their relative distance to the camera by analyzing the...
We propose a novel approach for compressed domain copy detection of scalable videos stored in a database. We analyze compressed H.264/SVC streams and form different scalable low-level and mid-level feature vectors that are robust to multiple transformations. The features are based on easily available information like the encoding bit rate over time and the motion vectors found in the stream. The focus...
We present a simple and lightweight approach to scene analysis in the H.264/SVC domain. The method is entirely based on the motion vectors found in the compressed stream. Motion segmentation and object detection is performed after the estimation of the camera motion. Important object properties are calculated, which are used for object matching and trajectory estimation. The relative distance to the...
This paper presents a joint indexing-coding approach applied to global camera motion detection in the scalable H.264/SVC compressed domain. Our goal is to facilitate and to improve indexing in the MPEG compressed domain, if necessary by modifying the original coded stream, without losing compatibility with the standard. In frames with very noisy motion vector fields, we use the global motion information...
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