## 2 Related Work  
The PIR sensors are widely used in surveillance systems and automatic light switching systems as simple but reliable triggers [8,9]. They also have shown promising capabilities as low-cost camera enhancers in video surveillance systems. The work of [PERSON] _et al._[10] uses PIR sensors in conjunction with cameras to address privacy issues. PIR sensors are deployed in private rooms while cameras in public areas. [PERSON] _et al._[11] presented a person localization algorithm using an infrared ceiling sensor network for providing various personalized services in an office environment, which demonstrates the benefits of reducing camera deployment by introducing PIR sensors. In [12], a kind of platform for home surveillance is proposed. The platform includes an ARM processor together with a Web camera and a PIR sensor. The PIR sensor triggers the Web camera in presence of an intruder in order to capture and send a snapshot to a remote server. Other works present different approaches to perform human body tracking and identifying using only PIR sensors. As for tracking, [PERSON] _et al._[13] presented a human tracking system using a node with eight PIR detectors and Fresnel lens arrays arranged around a circle; and the system can be used to track single human target by detecting its angular displacement while moving. Similarly, the authors also introduced multiple human tracking and identification with wireless distributed PIR sensor systems. [PERSON] _et al._[14] developed a human tracking system using a low-cost sensor cluster consisting of PIR sensors and Fresnel lens arrays to implement the desired spatial segmentations. They analyzed the response characteristics of the sensor cluster, and extracted velocity and the direction of motion over large areas of more than 12 m. [PERSON] _et al._[15] presented a location-aware system, which uses an array of PIR sensors. In such system, the PIR sensors, on the ceiling with overlapping detective areas of adjacent sensors, can detect the presence of a resident. However, this system cannot work when there are multiple targets or it is deployed at vacant zones. In [PERSON] _et al_[16], four sensor modules, each of which consists of five PIR detectors, are mounted on the ceiling of a monitor field to fix the position of a moving human target. In addition, Kalman filter is adopted to improve the tracking accuracy. [PERSON] _et al._[17] developed a compressive multi-target tracking system used in binary PIR sensor networks. Each sensor node can detect multiple small regions instead of a large one in order to achieve high sensing resolution and efficiency. In terms of recognition, [PERSON] _et al._[18] presented a human identification system using a PIR sensor whose visibility is modulated by a Fresnel lens array and principal components regression method. They also presented a method for identifying subjects walking randomly by using PIR sensors with modulated visibilities and hidden Markov models [18, 19]. [PERSON] _et al._[20] developed a wireless distributed pyroelectric sensor system to recognize different walkers' gait features. [PERSON] _et al._[21] built a distributed binary pyroelectric sensor network (PSN) for the purpose of multi-walker recognition and tracking. They accurately extract context features from a hybrid, binary, multi-walker sensor data stream to identify and track multi-walker and achieve good results, in the four tested scenarios with 100% success rate. [PERSON] _et al._[22] used binary principle component analysis (B-PCA) to interpret the relationship between observed sensor data and hidden context patterns, and conducted comprehensive experiments from real sensor data to verify the context detection accuracy. [PERSON] _et al._[23] proposed a statistical subspace representation model called probabilistic nonnegative matrix factorization (PNMF) to seek the scenario patterns rather than the object characteristics. They further prove that their PNMF model is a generic model for nonnegative matrix factorization (NMF) based algorithms [24].