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Milad Ghanbari

dblp:161/1375 · DBLP profile ↗
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3ranked-venue papers
2as first author
3since 2021 · last 2025
0009-0005-5168-1664ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 3 · 2 first-author · 3 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Virtual and augmented reality · 87% Image and video coding · 13%
Human-computer interaction and pervasive computing
1 paper
Usability and user experience research · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Virtual and augmented reality
immersive video
0.912025
SVD: Spatial Video Dataset · ACM Multimedia 2025
Virtual and augmented reality › 3d video
stereoscopic video
0.912025
SVD: Spatial Video Dataset · ACM Multimedia 2025
Image and video coding › multiview video coding
stereo video coding
0.312025
SVD: Spatial Video Dataset · ACM Multimedia 2025
Usability and user experience research
quality of experience
0.312025
SDART: Spatial Dart AR Simulation with Hand-Tracked Input · ACM Multimedia 2025

Methods — techniques the papers use, named apart from their topics

subjective questionnaire · 0.9stereoscopic capture pipeline · 0.9physics simulation · 0.9hand tracking · 0.9
YearPublicationVenuePosition
2025 SDART: Spatial Dart AR Simulation with Hand-Tracked Input
abstract
We present a physics-driven 3D dart-throwing interaction system for Apple Vision Pro (AVP), developed using Unity 6 engine and running in augmented reality (AR) mode on the device. The system utilizes the PolySpatial and Apple's ARKit software development kits (SDKs) to ensure hand input and tracking in order to intuitively spawn, grab, and throw virtual darts similar to real darts. The application benefits from physics simulations alongside the innovative no-controller input system of AVP to manipulate objects realistically in an unbounded spatial volume. By implementing spatial distance measurement, scoring logic, and recording user performance, this project enables user studies on quality of experience in interactive experiences. To evaluate the perceived quality and realism of the interaction, we conducted a subjective study with 10 participants using a structured questionnaire. The study measured various aspects of the user experience, including visual and spatial realism, control fidelity, depth perception, immersiveness, and enjoyment. Results indicate high mean opinion scores (MOS) across key dimensions.
Milad Ghanbari, Wei Zhou 0021, Cosmin Stejerean, Christian Timmerer, Hadi Amirpour
ACM Multimedia1
2025 SVD: Spatial Video Dataset
abstract
Stereoscopic video has long been the subject of research due to its ability to deliver immersive three-dimensional content to a wide range of applications. The dual-view format inherently provides binocular disparity cues that enhance depth perception and realism, making it indispensable for fields such as telepresence, 3D mapping, and robotic vision. Until recently, however, end-to-end pipelines for capturing, encoding, and viewing high-quality stereoscopic video were neither widely accessible nor optimized for consumer-grade devices. Today's smartphones, such as the iPhone Pro, and modern Head-Mounted Displays (HMDs) like the Apple Vision Pro, offer built-in support for stereoscopic video capture, hardware-accelerated encoding, and seamless playback on devices like the Apple Vision Pro and Meta Quest 3, which require minimal user intervention. Apple refers to this streamlined workflow as spatial Video. Making the full stereoscopic video process available to everyone has made new applications possible. Despite these advances, there remains a notable absence of publicly available datasets that include the complete spatial video pipeline on consumer platforms, hindering reproducibility and comparative evaluation of emerging algorithms.
Mohammad Hossein Izadimehr, Milad Ghanbari, Guodong Chen 0004, Wei Zhou 0021, Xiaoshuai Hao, Mallesham Dasari, Christian Timmerer, Hadi Amirpour
ACM Multimedia2
2025 STACK: Spatial Tower Assembly using Controlled Kinetics
abstract
This paper presents a block stacking simulation developed for Apple Vision Pro (AVP) using Unity’s PolySpatial framework, designed to study both depth perception in spatial computing and physics comprehension of user-driven kinetic controls in augmented reality (AR). The simulation offers two interactive modes: a tower assembly mode and a removal mode. Each game session includes four stages with the virtual table positioned at various distances to observe user adaptation across varying virtual depths. User input is captured through eye tracking and hand tracking, and block behavior is handled by real-time physics simulation, which includes collision response, gravity, and mass-based interactions. The system supports two physics configurations: raw Unity physics and a modified variant with adjusted material and rigidbody parameters for improved stability and realism. It utilizes spatial computing features such as world anchoring to preserve spatial consistency and depth perception through stereoscopic rendering and dynamic shadows, so that users can better judge the spatial coordinates between virtual blocks and their physical surroundings. The simulation is intended to evaluate how 3D spatial rendering and physically realistic interactions contribute to immersion and task performance in AR environments. To assess user performance, the system records key interaction metrics to support analysis of learning progression, control accuracy, and adaptability across varying distances and physics configurations. This work contributes to the understanding of spatial and physics-based interaction design in AR and may inform future applications in education, simulation, and spatial gaming.
Milad Ghanbari, Hadi Amirpour, Christian Timmerer, Mohammad Hossein Izadimehr, Wei Zhou 0021, Cosmin Stejerean
VCIP1