GMCP-Tracker: Global Multi-object Tracking Using Generalized Minimum Clique Graphs UCF Problem: 4. Tracking by Detection Key Contributions: A new tool in Computer Vision: Generalized Minimum Clique Problem (GMCP): Typically useful where there are multiple possibilities for some subproblems, as well as a global criterion to satisfy. GMCP utilized for computing tracklets and trajectories. A new temporally global approach to Data Association A new tracklet-global motion cost model. Shifting approximation from Time Domain to Object Domain: Finding tracklets/trajectories in a temporally global way. Finding the tracklet/trajectory of one object at a time (greedy). 𝑣21 𝑣12 𝐶2 𝑣22 𝑣14 𝑣23 𝑣32 𝑣31 𝐶4 Trajectories 𝑣13 𝐶3 𝐶5 𝑣15 𝑣25 𝑣24 𝑣34 𝑣35 𝐶6 ECCV ‘12 Found Tracklets in Different Segments: Frame 3 𝑣33 𝑣𝟒6 𝑣16 𝑣26 𝑣36 5. Frame 4 Frame 5 Frame 6 Frame 1 Frame 2 Frame 3 Input Graph G • Frame 2 𝑣11 𝐶1 ({aroshan| adehghan | shah @cs.ucf.edu} , University of Central Florida) Finding Tracklets Using GMCP: Frame 1 Input Detections 1. Amir Roshan Zamir, Afshin Dehghan, Mubarak Shah Merging Tracklets into Trajectories: Input Tracklets • Tracklet-global Motion Cost Model 6. Experimental Results Minimum Clique Occlusion Handling using HN Bipartite Matching vs. GMCP Frame 5 Frame 6 Frame 1 Frame 2 Frame 3 Block Diagram: 3. Generalized Minimum Clique Problem (GMCP): Input to GMCP Generalized Minimum Clique Fra me 2 Minimum Clique 2. Frame 4 Fra me 5 Frame 4 Frame 1 (nodes≡detections) (clusters≡frames) (GMCP solution=tracklet of one Object) • Occlusion Handling Using Hypothetical Nodes: Project Page Definition: Frame 3 Project Page: http://vision.eecs.ucf.edu/ projects/GMCP-Tracker/ YouTube 𝐺𝑠 = (𝑽𝑠 , 𝑬𝑠 , 𝑤𝑠 ) Frame 2 Frame 6 Occlusion Handling Using HN 𝐺 = (𝑽, 𝑬, 𝑤) Frame 5 Frame 4 Frame 5 Frame 6
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