# Region Graph Based Method for Multi-Object Detection and Tracking using Depth Cameras

Source: [Region Graph Based Method for Multi-Object Detection and Tracking using Depth Cameras](<https://www.sota2.com/research/paper/68fa62621e209131ce9f8fce>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T20:18:31.734Z

Authors: Sachin Mehta, Balakrishnan Prabhakaran

Published: 2016-03-11T21:06:35.000Z

## Abstract

In this paper, we propose a multi-object detection and tracking method using depth cameras. Depth maps are very noisy and obscure in object detection. We first propose a region-based method to suppress high magnitude noise which cannot be filtered using spatial filters. Second, the proposed method detect Region of Interests by temporal learning which are then tracked using weighted graph-based approach. We demonstrate the performance of the proposed method on standard depth camera datasets with and without object occlusions. Experimental results show that the proposed method is able to suppress high magnitude noise in depth maps and detect/track the objects (with and without occlusion).

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1603.03783>)

[PDF](<https://arxiv.org/pdf/1603.03783.pdf>)
