In stereoscopic displays different images are presented separately to the left and right eyes. This requirement may increase the bandwidth demand as well as increase the occurrence of visible compression-related artefacts. Here we report the results of a large-scale subjective assessment of high dynamic range (HDR) stereoscopic image compression. The ISO/IEC 29170-2 flicker paradigm was adapted for stereoscopic images and used to evaluate two VESA (Video Electronics Standards Association) image compression codecs: DSC 1.2a and VDCM 1.2.2. We compared the performance on stereoscopic images versus 2D images for both codecs.

Reliable wide-field detection of human activity is an unsolved problem. The main difficulty is that low resolution and the unconstrained nature of realistic environments and human behaviour make form cues unreliable. Here we argue that reliability in far- or wide-field detection can still be achieved by probabilistic combination of multiple weak but complementary visual cues that do not depend on detailed form analysis. To demonstrate, we describe a real-time Bayesian algorithm for localizing human activity in relatively unconstrained scenes, using motion, background subtraction and skin colour cues. Fast sampling of scale space is achieved using integral images and a flexible norm that can handle sparse cues without loss of statistical power. We show that the probabilistic approach far outperforms a representative logical approach in which skin and background subtraction classifiers are combined conjunctively. Our method is currently used in a pre-attentive human activity sensor, generating saccadic targets for an attentive foveated vision system that reliably fixates faces over a 130 deg field of view, allowing high-resolution capture of facial images over a large dynamic scene.