Guanzhou Ji

Guanzhou Ji, Azadeh O. Sawyer, Srinivasa G. Narasimhan

We propose a novel inverse rendering method that enables the transformation of existing indoor panoramas with new indoor furniture layouts under natural illumination. To achieve this, we captured indoor HDR panoramas along with real-time outdoor hemispherical HDR photographs. Indoor and outdoor HDR images were linearly calibrated with measured absolute luminance values for accurate scene relighting. Our method consists of three key components: (1) panoramic furniture detection and removal, (2) automatic floor layout design, and (3) global rendering with scene geometry, new furniture objects, and a real-time outdoor photograph. We demonstrate the effectiveness of our workflow in rendering indoor scenes under different outdoor illumination conditions. Additionally, we contribute a new calibrated HDR (Cali-HDR) dataset that consists of 137 calibrated indoor panoramas and their associated outdoor photographs.

Guanzhou Ji, Tingsong Ou, Azadeh O. Sawyer · cmu

This paper introduces a novel computational method for mapping indoor luminance values on the facade of an open workplace to improve its daylight performance. 180-degree fisheye renderings from different indoor locations, view positions, and times of the year are created. These renderings are then transformed from two-dimensional (2D) images into three-dimensional (3D) hemispheres. High luminance values are filtered and projected from the hemisphere to the facade surface. This framework will highlight the areas of the facade that allow too much light penetration into the interior environment. The flexible workflow allows occupant centric lighting analysis that computes multiple design parameters and synthesizes results for localized facade optimization and daylight design.

Zining Cheng, Guanzhou Ji

This paper presents the use of panoramic 3D estimation in lighting simulation. Conventional lighting simulation necessitates detailed modeling as input, resulting in significant labor effort and time cost. The 3D layout estimation method directly takes a single panorama as input and generates a lighting simulation model with room geometry and window aperture. We evaluate the simulation results by comparing the luminance errors between on-site High Dynamic Range (HDR) photographs, 3D estimation model, and detailed model in panoramic representation and fisheye perspective. Given the selected scene, the results demonstrate the estimated room layout is reliable for lighting simulation.

Guanzhou Ji, Sriram Narayanan, Azadeh Sawyer et al.

This paper introduces a novel image-based rendering technique for jointly estimating indoor lighting and thermal conditions from paired indoor-outdoor high dynamic range (HDR) panoramas. Our method uses the indoor panorama to estimate the 3D floor layout, while the corresponding outdoor panorama serves as an environment map to infer spatially-varying illumination and material properties. Assuming indoor surfaces are Lambertian and that all heat originates from outdoor visible light, we model the relationship between light transport and heat transfer, and perform transient heat simulations to generate indoor temperature distributions. The simulated heat maps are validated against real-world thermal images captured with an infrared camera. This approach supports photorealistic and physically informed visualization, enabling integrated light and heat estimation to advance traditional virtual home staging.