Textureless Deformable Object Tracking with Invisible Markers.

Tracking and reconstructing deformable objects with little texture is challenging due to the lack of features. Here we introduce "invisible markers" for accurate and robust correspondence matching and tracking. Our markers are visible only under ultraviolet (UV) light.

Polarimetric Helmholtz Stereopsis.

Helmholtz stereopsis (HS) exploits the reciprocity principle of light propagation (i.e., the Helmholtz reciprocity) for 3D reconstruction of surfaces with arbitrary reflectance.

Multi-frequency acoustic hologram generation with a physics-enhanced deep neural network.

Here, a physics-enhanced multi-frequency acoustic hologram deep neural network (PhysNet_MFAH) method is proposed for designing multi-frequency acoustic holograms, which is built by incorporating multiple physical models that represent the physical processes of acoustic waves propagation for a set of design frequencies into a deep neural network. It is demonstrated that one needs only to feed a set of frequency-specific target patterns into the network, the proposed PhysNet_MFAH method can automatically, accurately, and rapidly generate a high-quality multi-frequency acoustic hologram for holographic rendering of different target acoustic fields in the same or distinct regions of the target plane when driven at different frequencies. Remarkably, it is also demonstrated that the proposed PhysNet_MFAH method can achieve a higher quality of the reconstructed acoustic intensity fields than the existing optimization methods IASA and DS for designing multi-frequency acoustic holograms at a relatively fast-computational speed.

Shape and Reflectance Reconstruction Using Concentric Multi-Spectral Light Field.

Recovering the shape and reflectance of non-Lambertian surfaces remains a challenging problem in computer vision since the view-dependent appearance invalidates traditional photo-consistency constraint. In this paper, we introduce a novel concentric multi-spectral light field (CMSLF) design that is able to recover the shape and reflectance of surfaces of various materials in one shot. Our CMSLF system consists of an array of cameras arranged on concentric circles where each ring captures a specific spectrum.

Content Aware Image Pre-Compensation.

The goal of image pre-compensation is to process an image such that after being convolved with a known kernel, will appear close to the sharp reference image. In a practical setting, the pre-compensated image has significantly higher dynamic range than the latent image. As a result, some form of tone mapping is needed.

Assessing the impacts of the changes in farming systems on food security and environmental sustainability of a Chinese rural region under different policy scenarios: an agent-based model.

Since China has undergone a series of economic reforms and implemented opening up policies, its farming systems have significantly changed and have dramatically influenced the society, economy, and environment of China. To assess the comprehensive impacts of these changes on food security and environmental sustainability, and establish effective and environment-friendly subsidy policies, this research constructed an agent-based model (ABM). Daligang Town, which is located in the two-season rice region of Southern China, was selected as the case study site.

Assessing the effects of rural livelihood transition on non-point source pollution: a coupled ABM-IECM model.

Water pollution caused by anthropogenic activities and driven by changes in rural livelihood strategies in an agricultural system has received increasing attention in recent decades. To simulate the effects of rural household livelihood transition on non-point source (NPS) pollution, a model combining an agent-based model (ABM) and an improved export coefficient model (IECM) was developed. The ABM was adopted to simulate the dynamic process of household livelihood transition, and the IECM was employed to estimate the effects of household livelihood transition on NPS pollution.

Saliency Detection on Light Field.

Existing saliency detection approaches use images as inputs and are sensitive to foreground/background similarities, complex background textures, and occlusions. We explore the problem of using light fields as input for saliency detection. Our technique is enabled by the availability of commercial plenoptic cameras that capture the light field of a scene in a single shot.