Search

Non-line-of-sight (NLOS) imaging is attractive for its potential applications in autonomous vehicles, robotic vision, and biomedical imaging. NLOS imaging can be realized through reconstruction or recognition. Recognition is preferred in some practical scenarios because it can classify hidden objects directly and quickly. Current NLOS recognition is mostly realized by exploiting active laser illumination. However, passive NLOS recognition, which is essential for its simplified hardware system and good stealthiness, has not been explored. Here, we use a passive imaging setting that consists of a standard digital camera and an occluder to achieve a NLOS recognition system by deep learning. The proposed passive NLOS recognition system demonstrates high accuracy with the datasets of handwritten digits, hand gestures, human postures, and fashion products (81.58 % to 98.26%) using less than 1 second per image in a dark room. Beyond, good performance can be maintained under more complex lighting conditions and practical tests. Moreover, we conversely conduct white-box attacks on the NLOS recognition algorithm to study its security. An attack success rate of approximately 36% is achieved at a relatively low cost, which demonstrates that the existing passive NLOS recognition remains somewhat vulnerable to small perturbations. Non-line-of-sight imaging allows reconstruction and recognition of an obscured object, but external manipulation of the data can lead to inaccurate results. Here, the accuracy and robustness of passive non-line-of-sight recognition and its fragility to adversarial attacks are studied.

In order to enhance the absorption of phase change materials in specific spectral range, a novel compact structure based on surface plasmon resonance is proposed, which is composed of vanadium dioxide (VO2) film and Au-disk structure. Simulation results show that the absorption peak at λ=4.0μm with the full width at half maximum is only about 100nm, and the dependence on the structure parameters are analyzed in detail. Because the resistivity changes greatly during the phase transition of VO2, the detection of a specific spectrum can be completed by signal detection. Our study can be used in the development of new mid-infrared thermal detectors and active control devices.

Electrochromic devices with tunable infrared radiation can meet the steadily growing demands in energy saving and thermal camouflage applications. Here, a mid-infrared radiation modulator based on flexible multilayer graphene thin films gated by nonvolatile ionic liquid on both rigid and flexible substrates is designed. The thermal emissivity of the device decreases nearly 80% within 2 s with the accumulation of anions in the multilayer graphene. The effective reduction of the emissivity results from the dramatic decrease in film's intraband absorption of graphene according to the Drude model. It has been demonstrated that with electrical control the film's mid-infrared radiation is capable of adapting to different backgrounds for thermal camouflage applications. Moreover, a sandwiched structure with stacked graphene films is designed to realize structural flexibility and double-sided radiation control for a wide range of potential applications, including energy-efficient buildings, infrared sources, and electrochromic displays.