Task 1: Multi-scale Object Detection

Task 2: Long-term Multi-object Tracking

Task 3: Group Classification

798,000,000

Pixels (Max)

13

Natural Life Scenes

104,196

Head points

121,027

Bounding Boxes

News

GigaCamera System Introduction

UnstructuredCam

Gigapixel videography, beyond the resolution of single camera and human visual perception, plays an important role in capturing large-scale dynamic scene with extremely high resolution for both macro and micro domains. Restricted by the spatial-temporal bandwidth product of optical system, the size, weight, power and cost are central challenges in gigapixel video.

The UnstructuredCam we designed, an end-to-end unstructured multi-scale camera system, shows the ability of real-time capture, dynamically adjusting local-view cameras, and online warping for synthesizing gigapixel video. We take the advantage of our UnstructuredCam to develop the Tsinghua Gigapixel Dataset. And these datasets we provide in www.gigacamera.com are all characterized by extremely high resolution, large scale and wide FOV. We hope that our datasets will help researchers explore the cutting-edge computer vision tasks such as long-term multi-target object tracking, large-scale crowd counting, large-scale generic object detection, etc. » Continue Reading

Fig.1 Illustration of representative imaging systems. (a) single camera imaging system faces the contradiction between wide FOV and high resolution, (b) single-scale camera array imaging [1][2] relies on image stitching[3], (c) structured multi-scale camera array (AWARE2[4]) adopts two-stage optical imaging design, (d) un-structured multi-scale camera array (denoted as UnstructuredCam).

Project Demo Videoes

Live Demo of UnstructuredCam

Dataset Image Gallery

• Sequence ID: OCT Bay
• Image size: 26753 x 15052
• Frame rate: 30 Hz

• Sequence ID: Shanghai Train Station
• Image size: 26558 x 14828
• Frame rate: 30 Hz

• Sequence ID: Nanshan I Park
• Image size: 32609 x 24457
• Frame rate: 12 Hz

• Sequence ID: Primary School
• Image size: 31760 x 23810
• Frame rate: 12 Hz

• Sequence ID: Basketball Court
• Image size: 31753 x 23810
• Frame rate: 12 Hz

• Sequence ID: HIT Canteen
• Image size: 26753 x 15052
• Frame rate: 30 Hz

• Sequence ID: Shanghai Marathon
• Image size: 26908 x 15024
• Frame rate: 30 Hz

• Sequence ID: Shenzhenbei Station
• Image size: 26583 x 14957
• Frame rate: 30 Hz

• Sequence ID: Shenzhen Library
• Image size: 32129 x 24096
• Frame rate: 30 Hz

• Sequence ID: Xili Pedestrian Street
• Image size: 26583 x 14957
• Frame rate: 30 Hz

• Sequence ID: Xili Crossroad
• Image size: 26753 x 15052
• Frame rate: 30 Hz

Professors in Our Team

Lu Fang

Tsinghua University

Qionghai Dai

Tsinghua University

David J. Brady

Duke University
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