Appearance-based visual learning and object recognition with illumination invariance
Machine Vision and Applications - special issue on high performance computing for industrial visual inspection
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Vision and Applications
Adaptive probabilistic tracking embedded in smart cameras for distributed surveillance in a 3D model
EURASIP Journal on Embedded Systems
Multicamera People Tracking with a Probabilistic Occupancy Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
System and software architectures of distributed smart cameras
ACM Transactions on Embedded Computing Systems (TECS)
Feature-level information fusion methods for urban surveillance using heterogeneous sensor networks
Feature-level information fusion methods for urban surveillance using heterogeneous sensor networks
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With the technology advancements in wireless sensor networks and embedded cameras, distributed smart camera networks are emerging for surveillance applications. Wireless networks, however, introduce bandwidth constraints that need to be considered. Existing approaches for target tracking typically utilize target handover mechanisms between cameras or combine results from 2D trackers into 3D target estimation. Such approaches suffer from scale selection, target rotation, and occlusion, drawbacks associated with 2D tracking. This paper presents an approach for tracking multiple targets in 3D space using a network of smart cameras. The approach employs multi-view histograms to characterize targets in 3D space using color and texture as the visual features. The visual features from each camera, along with the target models are used in a probabilistic tracker to estimate the target state. One of the main innovations in the proposed tracker is in-network aggregation in order to reduce communication cost. The effectiveness of the proposed approach is demonstrates using a camera network deployed in a building.