Research Article

Nonnegative Matrix Factorizations Performing Object Detection and Localization

Table 2

Algorithm performances in terms of 𝑟 𝑒 𝑐 𝑎 𝑙 𝑙 and 𝑝 𝑟 𝑒 𝑐 𝑖 𝑠 𝑖 𝑜 𝑛 when applied to CarData with factor ranks 𝑟 = 2 0 and 𝑟 = 1 1 0 . Bold fonts indicate the highest values of precision and recall.

           𝑟 = 2 0
Method 𝑇 𝑃 𝐹 𝑃 R e c a l l P r e c i s i o n F-measure

NMF103 67 0.52 0.61 0.56
LNMF 92 78 0.46 0.54 0.5
NMFsc 106 640.530.620.57
DLPP 37 133 0.19 0.22 0.2

           𝑟 = 1 1 0
Method 𝑇 𝑃 𝐹 𝑃 R e c a l l P r e c i s i o n F-measure

NMF 112 580.560.660.61
LNMF 86 85 0.43 0.5 0.46
NMFsc 110 60 0.55 0.65 0.59
DLPP 21 93 0.11 0.18 0.13