Camera Networks: The Acquisition and Analysis of Videos over Wide Areas (Paperback)

As networks of video cameras are installed in many applications like security and surveillance, environmental monitoring, disaster response, and assisted living facilities, among others, image understanding in camera networks is becoming an important area of research and technology development. There are many challenges that need to be addressed in the process. Some of them are listed below:

- Traditional computer vision challenges in tracking and recognition, robustness to pose, illumination, occlusion, clutter, recognition of objects, and activities;

- Aggregating local information for wide area scene understanding, like obtaining stable, long-term tracks of objects;

- Positioning of the cameras and dynamic control of pan-tilt-zoom (PTZ) cameras for optimal sensing;

- Distributed processing and scene analysis algorithms;

- Resource constraints imposed by different applications like security and surveillance, environmental monitoring, disaster response, assisted living facilities, etc.

In this book, we focus on the basic research problems in camera networks, review the current state-of-the-art and present a detailed description of some of the recently developed methodologies. The major underlying theme in all the work presented is to take a network-centric view whereby the overall decisions are made at the network level. This is sometimes achieved by accumulating all the data at a central server, while at other times by exchanging decisions made by individual cameras based on their locally sensed data.

Chapter One starts with an overview of the problems in camera networks and the major research directions. Some of the currently available experimental testbeds are also discussed here. One of the fundamental tasks in the analysis of dynamic scenes is to track objects. Since camera networks cover a large area, the systems need to be able to track over such wide areas where there could be both overlapping and non-overlapping fields of view of the cameras, as addressed in Chapter Two: Distributed processing is another challenge in camera networks and recent methods have shown how to do tracking, pose estimation and calibration in a distributed environment. Consensus algorithms that enable these tasks are described in Chapter Three. Chapter Four summarizes a few approaches on object and activity recognition in both distributed and centralized camera network environments. All these methods have focused primarily on the analysis side given that images are being obtained by the cameras. Efficient utilization of such networks often calls for active sensing, whereby the acquisition and analysis phases are closely linked. We discuss this issue in detail in Chapter Five and show how collaborative and opportunistic sensing in a camera network can be achieved. Finally, Chapter Six concludes the book by highlighting the major directions for future research.

Table of Contents: An Introduction to Camera Networks / Wide-Area Tracking / Distributed Processing in Camera Networks / Object and Activity Recognition / Active Sensing / Future Research Directions

隨著許多應用領域（如安全監控、環境監測、災害應對和輔助生活設施等）中安裝了視頻攝像機網絡，攝像機網絡中的圖像理解正成為一個重要的研究領域和技術發展領域。在這個過程中需要解決許多挑戰，其中一些列舉如下：
- 在追踪和識別中的傳統計算機視覺挑戰，如姿態、光照、遮擋、雜亂、對象和活動的識別的魯棒性；
- 聚合局部信息以實現廣域場景理解，例如獲取對象的穩定、長期軌跡；
- 攝像機的定位和全景傾斜變焦（PTZ）攝像機的動態控制，以實現最佳感知；
- 分散處理和場景分析算法；
- 不同應用（如安全監控、環境監測、災害應對、輔助生活設施等）所施加的資源限制。

在本書中，我們專注於攝像機網絡中的基礎研究問題，回顧當前的最新技術發展狀況，並詳細介紹一些最近開發的方法。所有所呈現的工作的主要主題是以網絡為中心的觀點，即整體決策是在網絡層面上進行的。有時通過在中央服務器上累積所有數據來實現，而有時則通過根據攝像機的本地感知數據進行的個別攝像機的決策交換來實現。

第一章首先概述了攝像機網絡中的問題和主要研究方向。同時還討論了目前可用的實驗測試平台之一。在動態場景分析中的一個基本任務是追踪對象。由於攝像機網絡覆蓋了廣大區域，系統需要能夠在這樣的廣域範圍內進行追踪，其中攝像機的視野既有重疊又有非重疊，這在第二章中有所討論。分散處理是攝像機網絡中的另一個挑戰，最近的方法展示了如何在分散環境中進行追踪、姿態估計和校準。實現這些任務的共識算法在第三章中描述。第四章總結了分散和集中攝像機網絡環境中的一些對象和活動識別方法。所有這些方法主要關注分析方面，因為圖像是由攝像機獲取的。有效利用這樣的網絡通常需要主動感知，即獲取和分析階段密切相關。我們在第五章中詳細討論了這個問題，並展示了如何實現攝像機網絡中的協作和機會感知。最後，第六章通過強調未來研究的主要方向來總結本書。

目錄：攝像機網絡簡介 / 廣域追踪 / 攝像機網絡中的分散處理 / 對象和活動識別 / 主動感知 / 未來研究方向