24 Result(s)
within
Chapter
Andrea Cavallaro
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Chapter and Conference Paper
Cross-Camera View-Overlap Recognition
We propose a decentralised view-overlap recognition framework that operates across freely moving cameras without the need of a reference 3D map. Each camera independently extracts, aggregates into a hierarchic...
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Chapter and Conference Paper
Novel-View Human Action Synthesis
Novel-View Human Action Synthesis aims to synthesize the movement of a body from a virtual viewpoint, given a video from a real viewpoint. We present a novel 3D reasoning to synthesize the target viewpoint. We...
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Chapter and Conference Paper
Motion Prediction for First-Person Vision Multi-object Tracking
Tracking multiple independently moving objects with cameras mounted on moving robots is becoming increasingly common. However, most causal trackers rely on linear motion models that may be inaccurate in these ...
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Chapter and Conference Paper
A First-Person Vision Dataset of Office Activities
We present a multi-subject first-person vision dataset of office activities. The dataset contains the highest number of subjects and activities compared to existing office activity datasets. Office activities ...
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Chapter and Conference Paper
Description and Recognition of Activity Patterns Using Sparse Vector Fields
Far-field activities represented as time series or trajectories can be summarized in compact representations of frequent patterns. Popular representations such as clustering or probabilistic modeling of trajec...
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Chapter and Conference Paper
An Online Platform for Underwater Image Quality Evaluation
With the miniaturisation of underwater cameras, the volume of available underwater images has been considerably increasing. However, underwater images are degraded by the absorption and scattering of light in ...
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Chapter and Conference Paper
Pose Guided Human Image Synthesis by View Disentanglement and Enhanced Weighting Loss
View synthesis aims at generating a novel, unseen view of an object. This is a challenging task in the presence of occlusions and asymmetries. In this paper, we present View-Disentangled Generator (VDG), a two...
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Chapter and Conference Paper
Residual Stacked RNNs for Action Recognition
Action recognition pipelines that use Recurrent Neural Networks (RNN) are currently 5–10% less accurate than Convolutional Neural Networks (CNN). While most works that use RNNs employ a 2D CNN on each frame to...
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Chapter and Conference Paper
Erratum to: Video Analytics
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Chapter and Conference Paper
Online Multi-target Tracking with Strong and Weak Detections
We propose an online multi-target tracker that exploits both high- and low-confidence target detections in a Probability Hypothesis Density Particle Filter framework. High-confidence (strong) detections are us...
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Chapter and Conference Paper
Pop-up Modelling of Hazy Scenes
This paper describes the construction of a layered scene-model, based on a single hazy image of an outdoor scene. A depth map and radiance image are estimated by standard dehazing methods. The radiance image i...
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Chapter and Conference Paper
Probabilistic Subpixel Temporal Registration for Facial Expression Analysis
Face images in a video sequence should be registered accurately before any analysis, otherwise registration errors may be interpreted as facial activity. Subpixel accuracy is crucial for the analysis of subtle...
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Chapter
Towards Cognitive and Perceptive Video Systems
In this chapter we cover research and development issues related to smart cameras. We discuss challenges, new technologies and algorithms, applications and the evaluation of today’s technologies. We will cover...
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Chapter
Simultaneous Detection and Tracking with Multiple Cameras
Tracking targets using multiple cameras is an important processing step for applications such as sports analysis, traffic monitoring, behavior detection and event recognition. The multi-camera tracking problem...
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Chapter
Multi-view Multi-object Detection and Tracking
Multi-viewtrackers combine data fromdifferent camera views to estimate the temporal evolution of objects across a monitored area. Data to be combined can be represented by object features (such as position, co...
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Chapter
Change Detection for Object Segmentation
Object segmentation based on motion or change detection is the first step in many smart camera applications, such as video surveillance, human computer interaction, and immersive gaming. Efficient and accurate...
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Chapter
Recognizing Interactions in Video
Detection and tracking algorithms generates useful information in the form of trajectories from which the behaviors and the interactions of moving objects can be inferred through the analysis of spatio-tempora...
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Chapter
Trajectory Clustering for Scene Context Learning and Outlier Detection
We present a scene understanding strategy for video sequences based on clustering object trajectories. In this chapter, we discuss a set of relevant feature spaces for trajectory representation and we critical...
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Chapter and Conference Paper
Objective Evaluation of Pedestrian and Vehicle Tracking on the CLEAR Surveillance Dataset
Video object detection and tracking in surveillance scenarios is a difficult task due to several challenges caused by environmental variations, scene dynamics and noise introduced by the CCTV camera itself. In...
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Chapter and Conference Paper
Multi-feature Graph-Based Object Tracking
We present an object detection and tracking algorithm that addresses the problem of multiple simultaneous targets tracking in real-world surveillance scenarios. The algorithm is based on color change detection...
